| program(1.3) | |
| [buildInfo = dict<string, string>({{"coremlc-component-MIL", "3400.43.1"}, {"coremlc-version", "3400.58.2"}, {"coremltools-component-torch", "2.4.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.0"}})] | |
| { | |
| func main<ios18>(tensor<fp16, [1, 80, 3000]> logmel_data) { | |
| string var_32_pad_type_0 = const()[name = string("op_32_pad_type_0"), val = string("custom")]; | |
| tensor<int32, [2]> var_32_pad_0 = const()[name = string("op_32_pad_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [1]> var_32_strides_0 = const()[name = string("op_32_strides_0"), val = tensor<int32, [1]>([1])]; | |
| tensor<int32, [1]> var_32_dilations_0 = const()[name = string("op_32_dilations_0"), val = tensor<int32, [1]>([1])]; | |
| int32 var_32_groups_0 = const()[name = string("op_32_groups_0"), val = int32(1)]; | |
| tensor<fp16, [512, 80, 3]> weight_3_to_fp16 = const()[name = string("weight_3_to_fp16"), val = tensor<fp16, [512, 80, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))]; | |
| tensor<fp16, [512]> bias_3_to_fp16 = const()[name = string("bias_3_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(245888)))]; | |
| tensor<fp16, [1, 512, 3000]> var_32_cast_fp16 = conv(bias = bias_3_to_fp16, dilations = var_32_dilations_0, groups = var_32_groups_0, pad = var_32_pad_0, pad_type = var_32_pad_type_0, strides = var_32_strides_0, weight = weight_3_to_fp16, x = logmel_data)[name = string("op_32_cast_fp16")]; | |
| string input_1_mode_0 = const()[name = string("input_1_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 512, 3000]> input_1_cast_fp16 = gelu(mode = input_1_mode_0, x = var_32_cast_fp16)[name = string("input_1_cast_fp16")]; | |
| string var_50_pad_type_0 = const()[name = string("op_50_pad_type_0"), val = string("custom")]; | |
| tensor<int32, [2]> var_50_pad_0 = const()[name = string("op_50_pad_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [1]> var_50_strides_0 = const()[name = string("op_50_strides_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<int32, [1]> var_50_dilations_0 = const()[name = string("op_50_dilations_0"), val = tensor<int32, [1]>([1])]; | |
| int32 var_50_groups_0 = const()[name = string("op_50_groups_0"), val = int32(1)]; | |
| tensor<fp16, [512, 512, 3]> weight_7_to_fp16 = const()[name = string("weight_7_to_fp16"), val = tensor<fp16, [512, 512, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(246976)))]; | |
| tensor<fp16, [512]> bias_7_to_fp16 = const()[name = string("bias_7_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1819904)))]; | |
| tensor<fp16, [1, 512, 1500]> var_50_cast_fp16 = conv(bias = bias_7_to_fp16, dilations = var_50_dilations_0, groups = var_50_groups_0, pad = var_50_pad_0, pad_type = var_50_pad_type_0, strides = var_50_strides_0, weight = weight_7_to_fp16, x = input_1_cast_fp16)[name = string("op_50_cast_fp16")]; | |
| string x_3_mode_0 = const()[name = string("x_3_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 512, 1500]> x_3_cast_fp16 = gelu(mode = x_3_mode_0, x = var_50_cast_fp16)[name = string("x_3_cast_fp16")]; | |
| tensor<int32, [3]> var_56 = const()[name = string("op_56"), val = tensor<int32, [3]>([0, 2, 1])]; | |
| tensor<fp16, [1500, 512]> positional_embedding_to_fp16 = const()[name = string("positional_embedding_to_fp16"), val = tensor<fp16, [1500, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1820992)))]; | |
| tensor<fp16, [1, 1500, 512]> x_5_cast_fp16 = transpose(perm = var_56, x = x_3_cast_fp16)[name = string("transpose_60")]; | |
| tensor<fp16, [1, 1500, 512]> var_59_cast_fp16 = add(x = x_5_cast_fp16, y = positional_embedding_to_fp16)[name = string("op_59_cast_fp16")]; | |
| int32 var_72 = const()[name = string("op_72"), val = int32(-1)]; | |
| tensor<int32, [1]> var_88_axes_0 = const()[name = string("op_88_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_0_attn_ln_weight_to_fp16 = const()[name = string("blocks_0_attn_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3357056)))]; | |
| tensor<fp16, [512]> blocks_0_attn_ln_bias_to_fp16 = const()[name = string("blocks_0_attn_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3358144)))]; | |
| fp16 var_78_to_fp16 = const()[name = string("op_78_to_fp16"), val = fp16(0x1.5p-17)]; | |
| tensor<fp16, [1, 1500, 512]> var_88_cast_fp16 = layer_norm(axes = var_88_axes_0, beta = blocks_0_attn_ln_bias_to_fp16, epsilon = var_78_to_fp16, gamma = blocks_0_attn_ln_weight_to_fp16, x = var_59_cast_fp16)[name = string("op_88_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_99_to_fp16 = const()[name = string("op_99_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3359232)))]; | |
| tensor<fp16, [512]> var_100_to_fp16 = const()[name = string("op_100_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3883584)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_0_cast_fp16 = linear(bias = var_100_to_fp16, weight = var_99_to_fp16, x = var_88_cast_fp16)[name = string("linear_0_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_103_to_fp16 = const()[name = string("op_103_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3884672)))]; | |
| tensor<fp16, [512]> linear_1_bias_0_to_fp16 = const()[name = string("linear_1_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4409024)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_1_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_103_to_fp16, x = var_88_cast_fp16)[name = string("linear_1_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_107_to_fp16 = const()[name = string("op_107_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4410112)))]; | |
| tensor<fp16, [512]> var_108_to_fp16 = const()[name = string("op_108_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4934464)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_2_cast_fp16 = linear(bias = var_108_to_fp16, weight = var_107_to_fp16, x = var_88_cast_fp16)[name = string("linear_2_cast_fp16")]; | |
| tensor<int32, [4]> var_116 = const()[name = string("op_116"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_117_cast_fp16 = reshape(shape = var_116, x = linear_0_cast_fp16)[name = string("op_117_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_42_to_fp16 = const()[name = string("const_42_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> q_3_cast_fp16 = mul(x = var_117_cast_fp16, y = const_42_to_fp16)[name = string("q_3_cast_fp16")]; | |
| tensor<int32, [4]> var_123 = const()[name = string("op_123"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_124_cast_fp16 = reshape(shape = var_123, x = linear_1_cast_fp16)[name = string("op_124_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_43_to_fp16 = const()[name = string("const_43_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> k_3_cast_fp16 = mul(x = var_124_cast_fp16, y = const_43_to_fp16)[name = string("k_3_cast_fp16")]; | |
| tensor<int32, [4]> var_130 = const()[name = string("op_130"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_131_cast_fp16 = reshape(shape = var_130, x = linear_2_cast_fp16)[name = string("op_131_cast_fp16")]; | |
| tensor<int32, [4]> var_132 = const()[name = string("op_132"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| bool qk_1_transpose_x_0 = const()[name = string("qk_1_transpose_x_0"), val = bool(false)]; | |
| bool qk_1_transpose_y_0 = const()[name = string("qk_1_transpose_y_0"), val = bool(false)]; | |
| tensor<int32, [4]> transpose_24_perm_0 = const()[name = string("transpose_24_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; | |
| tensor<int32, [4]> transpose_25_perm_0 = const()[name = string("transpose_25_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])]; | |
| tensor<fp16, [1, 8, 64, 1500]> transpose_25 = transpose(perm = transpose_25_perm_0, x = k_3_cast_fp16)[name = string("transpose_57")]; | |
| tensor<fp16, [1, 8, 1500, 64]> transpose_24 = transpose(perm = transpose_24_perm_0, x = q_3_cast_fp16)[name = string("transpose_58")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> qk_1_cast_fp16 = matmul(transpose_x = qk_1_transpose_x_0, transpose_y = qk_1_transpose_y_0, x = transpose_24, y = transpose_25)[name = string("qk_1_cast_fp16")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> var_136_cast_fp16 = softmax(axis = var_72, x = qk_1_cast_fp16)[name = string("op_136_cast_fp16")]; | |
| bool var_138_transpose_x_0 = const()[name = string("op_138_transpose_x_0"), val = bool(false)]; | |
| bool var_138_transpose_y_0 = const()[name = string("op_138_transpose_y_0"), val = bool(false)]; | |
| tensor<fp16, [1, 8, 1500, 64]> v_3_cast_fp16 = transpose(perm = var_132, x = var_131_cast_fp16)[name = string("transpose_59")]; | |
| tensor<fp16, [1, 8, 1500, 64]> var_138_cast_fp16 = matmul(transpose_x = var_138_transpose_x_0, transpose_y = var_138_transpose_y_0, x = var_136_cast_fp16, y = v_3_cast_fp16)[name = string("op_138_cast_fp16")]; | |
| tensor<int32, [4]> var_139 = const()[name = string("op_139"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| tensor<int32, [3]> concat_0 = const()[name = string("concat_0"), val = tensor<int32, [3]>([1, 1500, 512])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_140_cast_fp16 = transpose(perm = var_139, x = var_138_cast_fp16)[name = string("transpose_56")]; | |
| tensor<fp16, [1, 1500, 512]> x_11_cast_fp16 = reshape(shape = concat_0, x = var_140_cast_fp16)[name = string("x_11_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_144_to_fp16 = const()[name = string("op_144_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4935552)))]; | |
| tensor<fp16, [512]> var_145_to_fp16 = const()[name = string("op_145_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5459904)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_3_cast_fp16 = linear(bias = var_145_to_fp16, weight = var_144_to_fp16, x = x_11_cast_fp16)[name = string("linear_3_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_13_cast_fp16 = add(x = var_59_cast_fp16, y = linear_3_cast_fp16)[name = string("x_13_cast_fp16")]; | |
| tensor<int32, [1]> var_152_axes_0 = const()[name = string("op_152_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_0_mlp_ln_weight_to_fp16 = const()[name = string("blocks_0_mlp_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5460992)))]; | |
| tensor<fp16, [512]> blocks_0_mlp_ln_bias_to_fp16 = const()[name = string("blocks_0_mlp_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5462080)))]; | |
| tensor<fp16, [1, 1500, 512]> var_152_cast_fp16 = layer_norm(axes = var_152_axes_0, beta = blocks_0_mlp_ln_bias_to_fp16, epsilon = var_78_to_fp16, gamma = blocks_0_mlp_ln_weight_to_fp16, x = x_13_cast_fp16)[name = string("op_152_cast_fp16")]; | |
| tensor<fp16, [2048, 512]> var_161_to_fp16 = const()[name = string("op_161_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5463168)))]; | |
| tensor<fp16, [2048]> var_162_to_fp16 = const()[name = string("op_162_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7560384)))]; | |
| tensor<fp16, [1, 1500, 2048]> linear_4_cast_fp16 = linear(bias = var_162_to_fp16, weight = var_161_to_fp16, x = var_152_cast_fp16)[name = string("linear_4_cast_fp16")]; | |
| string x_17_mode_0 = const()[name = string("x_17_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 1500, 2048]> x_17_cast_fp16 = gelu(mode = x_17_mode_0, x = linear_4_cast_fp16)[name = string("x_17_cast_fp16")]; | |
| tensor<fp16, [512, 2048]> var_167_to_fp16 = const()[name = string("op_167_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7564544)))]; | |
| tensor<fp16, [512]> var_168_to_fp16 = const()[name = string("op_168_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9661760)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_5_cast_fp16 = linear(bias = var_168_to_fp16, weight = var_167_to_fp16, x = x_17_cast_fp16)[name = string("linear_5_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_19_cast_fp16 = add(x = x_13_cast_fp16, y = linear_5_cast_fp16)[name = string("x_19_cast_fp16")]; | |
| int32 var_178 = const()[name = string("op_178"), val = int32(-1)]; | |
| tensor<int32, [1]> var_194_axes_0 = const()[name = string("op_194_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_1_attn_ln_weight_to_fp16 = const()[name = string("blocks_1_attn_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9662848)))]; | |
| tensor<fp16, [512]> blocks_1_attn_ln_bias_to_fp16 = const()[name = string("blocks_1_attn_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9663936)))]; | |
| fp16 var_184_to_fp16 = const()[name = string("op_184_to_fp16"), val = fp16(0x1.5p-17)]; | |
| tensor<fp16, [1, 1500, 512]> var_194_cast_fp16 = layer_norm(axes = var_194_axes_0, beta = blocks_1_attn_ln_bias_to_fp16, epsilon = var_184_to_fp16, gamma = blocks_1_attn_ln_weight_to_fp16, x = x_19_cast_fp16)[name = string("op_194_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_205_to_fp16 = const()[name = string("op_205_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9665024)))]; | |
| tensor<fp16, [512]> var_206_to_fp16 = const()[name = string("op_206_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10189376)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_6_cast_fp16 = linear(bias = var_206_to_fp16, weight = var_205_to_fp16, x = var_194_cast_fp16)[name = string("linear_6_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_209_to_fp16 = const()[name = string("op_209_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10190464)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_7_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_209_to_fp16, x = var_194_cast_fp16)[name = string("linear_7_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_213_to_fp16 = const()[name = string("op_213_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10714816)))]; | |
| tensor<fp16, [512]> var_214_to_fp16 = const()[name = string("op_214_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11239168)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_8_cast_fp16 = linear(bias = var_214_to_fp16, weight = var_213_to_fp16, x = var_194_cast_fp16)[name = string("linear_8_cast_fp16")]; | |
| tensor<int32, [4]> var_222 = const()[name = string("op_222"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_223_cast_fp16 = reshape(shape = var_222, x = linear_6_cast_fp16)[name = string("op_223_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_44_to_fp16 = const()[name = string("const_44_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> q_7_cast_fp16 = mul(x = var_223_cast_fp16, y = const_44_to_fp16)[name = string("q_7_cast_fp16")]; | |
| tensor<int32, [4]> var_229 = const()[name = string("op_229"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_230_cast_fp16 = reshape(shape = var_229, x = linear_7_cast_fp16)[name = string("op_230_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_45_to_fp16 = const()[name = string("const_45_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> k_7_cast_fp16 = mul(x = var_230_cast_fp16, y = const_45_to_fp16)[name = string("k_7_cast_fp16")]; | |
| tensor<int32, [4]> var_236 = const()[name = string("op_236"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_237_cast_fp16 = reshape(shape = var_236, x = linear_8_cast_fp16)[name = string("op_237_cast_fp16")]; | |
| tensor<int32, [4]> var_238 = const()[name = string("op_238"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| bool qk_3_transpose_x_0 = const()[name = string("qk_3_transpose_x_0"), val = bool(false)]; | |
| bool qk_3_transpose_y_0 = const()[name = string("qk_3_transpose_y_0"), val = bool(false)]; | |
| tensor<int32, [4]> transpose_26_perm_0 = const()[name = string("transpose_26_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; | |
| tensor<int32, [4]> transpose_27_perm_0 = const()[name = string("transpose_27_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])]; | |
| tensor<fp16, [1, 8, 64, 1500]> transpose_27 = transpose(perm = transpose_27_perm_0, x = k_7_cast_fp16)[name = string("transpose_53")]; | |
| tensor<fp16, [1, 8, 1500, 64]> transpose_26 = transpose(perm = transpose_26_perm_0, x = q_7_cast_fp16)[name = string("transpose_54")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> qk_3_cast_fp16 = matmul(transpose_x = qk_3_transpose_x_0, transpose_y = qk_3_transpose_y_0, x = transpose_26, y = transpose_27)[name = string("qk_3_cast_fp16")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> var_242_cast_fp16 = softmax(axis = var_178, x = qk_3_cast_fp16)[name = string("op_242_cast_fp16")]; | |
| bool var_244_transpose_x_0 = const()[name = string("op_244_transpose_x_0"), val = bool(false)]; | |
| bool var_244_transpose_y_0 = const()[name = string("op_244_transpose_y_0"), val = bool(false)]; | |
| tensor<fp16, [1, 8, 1500, 64]> v_7_cast_fp16 = transpose(perm = var_238, x = var_237_cast_fp16)[name = string("transpose_55")]; | |
| tensor<fp16, [1, 8, 1500, 64]> var_244_cast_fp16 = matmul(transpose_x = var_244_transpose_x_0, transpose_y = var_244_transpose_y_0, x = var_242_cast_fp16, y = v_7_cast_fp16)[name = string("op_244_cast_fp16")]; | |
| tensor<int32, [4]> var_245 = const()[name = string("op_245"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| tensor<int32, [3]> concat_1 = const()[name = string("concat_1"), val = tensor<int32, [3]>([1, 1500, 512])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_246_cast_fp16 = transpose(perm = var_245, x = var_244_cast_fp16)[name = string("transpose_52")]; | |
| tensor<fp16, [1, 1500, 512]> x_23_cast_fp16 = reshape(shape = concat_1, x = var_246_cast_fp16)[name = string("x_23_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_250_to_fp16 = const()[name = string("op_250_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11240256)))]; | |
| tensor<fp16, [512]> var_251_to_fp16 = const()[name = string("op_251_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11764608)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_9_cast_fp16 = linear(bias = var_251_to_fp16, weight = var_250_to_fp16, x = x_23_cast_fp16)[name = string("linear_9_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_25_cast_fp16 = add(x = x_19_cast_fp16, y = linear_9_cast_fp16)[name = string("x_25_cast_fp16")]; | |
| tensor<int32, [1]> var_258_axes_0 = const()[name = string("op_258_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_1_mlp_ln_weight_to_fp16 = const()[name = string("blocks_1_mlp_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11765696)))]; | |
| tensor<fp16, [512]> blocks_1_mlp_ln_bias_to_fp16 = const()[name = string("blocks_1_mlp_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11766784)))]; | |
| tensor<fp16, [1, 1500, 512]> var_258_cast_fp16 = layer_norm(axes = var_258_axes_0, beta = blocks_1_mlp_ln_bias_to_fp16, epsilon = var_184_to_fp16, gamma = blocks_1_mlp_ln_weight_to_fp16, x = x_25_cast_fp16)[name = string("op_258_cast_fp16")]; | |
| tensor<fp16, [2048, 512]> var_267_to_fp16 = const()[name = string("op_267_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11767872)))]; | |
| tensor<fp16, [2048]> var_268_to_fp16 = const()[name = string("op_268_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13865088)))]; | |
| tensor<fp16, [1, 1500, 2048]> linear_10_cast_fp16 = linear(bias = var_268_to_fp16, weight = var_267_to_fp16, x = var_258_cast_fp16)[name = string("linear_10_cast_fp16")]; | |
| string x_29_mode_0 = const()[name = string("x_29_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 1500, 2048]> x_29_cast_fp16 = gelu(mode = x_29_mode_0, x = linear_10_cast_fp16)[name = string("x_29_cast_fp16")]; | |
| tensor<fp16, [512, 2048]> var_273_to_fp16 = const()[name = string("op_273_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13869248)))]; | |
| tensor<fp16, [512]> var_274_to_fp16 = const()[name = string("op_274_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15966464)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_11_cast_fp16 = linear(bias = var_274_to_fp16, weight = var_273_to_fp16, x = x_29_cast_fp16)[name = string("linear_11_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_31_cast_fp16 = add(x = x_25_cast_fp16, y = linear_11_cast_fp16)[name = string("x_31_cast_fp16")]; | |
| int32 var_284 = const()[name = string("op_284"), val = int32(-1)]; | |
| tensor<int32, [1]> var_300_axes_0 = const()[name = string("op_300_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_2_attn_ln_weight_to_fp16 = const()[name = string("blocks_2_attn_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15967552)))]; | |
| tensor<fp16, [512]> blocks_2_attn_ln_bias_to_fp16 = const()[name = string("blocks_2_attn_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15968640)))]; | |
| fp16 var_290_to_fp16 = const()[name = string("op_290_to_fp16"), val = fp16(0x1.5p-17)]; | |
| tensor<fp16, [1, 1500, 512]> var_300_cast_fp16 = layer_norm(axes = var_300_axes_0, beta = blocks_2_attn_ln_bias_to_fp16, epsilon = var_290_to_fp16, gamma = blocks_2_attn_ln_weight_to_fp16, x = x_31_cast_fp16)[name = string("op_300_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_311_to_fp16 = const()[name = string("op_311_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15969728)))]; | |
| tensor<fp16, [512]> var_312_to_fp16 = const()[name = string("op_312_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16494080)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_12_cast_fp16 = linear(bias = var_312_to_fp16, weight = var_311_to_fp16, x = var_300_cast_fp16)[name = string("linear_12_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_315_to_fp16 = const()[name = string("op_315_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16495168)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_13_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_315_to_fp16, x = var_300_cast_fp16)[name = string("linear_13_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_319_to_fp16 = const()[name = string("op_319_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17019520)))]; | |
| tensor<fp16, [512]> var_320_to_fp16 = const()[name = string("op_320_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17543872)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_14_cast_fp16 = linear(bias = var_320_to_fp16, weight = var_319_to_fp16, x = var_300_cast_fp16)[name = string("linear_14_cast_fp16")]; | |
| tensor<int32, [4]> var_328 = const()[name = string("op_328"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_329_cast_fp16 = reshape(shape = var_328, x = linear_12_cast_fp16)[name = string("op_329_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_46_to_fp16 = const()[name = string("const_46_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> q_11_cast_fp16 = mul(x = var_329_cast_fp16, y = const_46_to_fp16)[name = string("q_11_cast_fp16")]; | |
| tensor<int32, [4]> var_335 = const()[name = string("op_335"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_336_cast_fp16 = reshape(shape = var_335, x = linear_13_cast_fp16)[name = string("op_336_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_47_to_fp16 = const()[name = string("const_47_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> k_11_cast_fp16 = mul(x = var_336_cast_fp16, y = const_47_to_fp16)[name = string("k_11_cast_fp16")]; | |
| tensor<int32, [4]> var_342 = const()[name = string("op_342"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_343_cast_fp16 = reshape(shape = var_342, x = linear_14_cast_fp16)[name = string("op_343_cast_fp16")]; | |
| tensor<int32, [4]> var_344 = const()[name = string("op_344"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| bool qk_5_transpose_x_0 = const()[name = string("qk_5_transpose_x_0"), val = bool(false)]; | |
| bool qk_5_transpose_y_0 = const()[name = string("qk_5_transpose_y_0"), val = bool(false)]; | |
| tensor<int32, [4]> transpose_28_perm_0 = const()[name = string("transpose_28_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; | |
| tensor<int32, [4]> transpose_29_perm_0 = const()[name = string("transpose_29_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])]; | |
| tensor<fp16, [1, 8, 64, 1500]> transpose_29 = transpose(perm = transpose_29_perm_0, x = k_11_cast_fp16)[name = string("transpose_49")]; | |
| tensor<fp16, [1, 8, 1500, 64]> transpose_28 = transpose(perm = transpose_28_perm_0, x = q_11_cast_fp16)[name = string("transpose_50")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> qk_5_cast_fp16 = matmul(transpose_x = qk_5_transpose_x_0, transpose_y = qk_5_transpose_y_0, x = transpose_28, y = transpose_29)[name = string("qk_5_cast_fp16")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> var_348_cast_fp16 = softmax(axis = var_284, x = qk_5_cast_fp16)[name = string("op_348_cast_fp16")]; | |
| bool var_350_transpose_x_0 = const()[name = string("op_350_transpose_x_0"), val = bool(false)]; | |
| bool var_350_transpose_y_0 = const()[name = string("op_350_transpose_y_0"), val = bool(false)]; | |
| tensor<fp16, [1, 8, 1500, 64]> v_11_cast_fp16 = transpose(perm = var_344, x = var_343_cast_fp16)[name = string("transpose_51")]; | |
| tensor<fp16, [1, 8, 1500, 64]> var_350_cast_fp16 = matmul(transpose_x = var_350_transpose_x_0, transpose_y = var_350_transpose_y_0, x = var_348_cast_fp16, y = v_11_cast_fp16)[name = string("op_350_cast_fp16")]; | |
| tensor<int32, [4]> var_351 = const()[name = string("op_351"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| tensor<int32, [3]> concat_2 = const()[name = string("concat_2"), val = tensor<int32, [3]>([1, 1500, 512])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_352_cast_fp16 = transpose(perm = var_351, x = var_350_cast_fp16)[name = string("transpose_48")]; | |
| tensor<fp16, [1, 1500, 512]> x_35_cast_fp16 = reshape(shape = concat_2, x = var_352_cast_fp16)[name = string("x_35_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_356_to_fp16 = const()[name = string("op_356_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17544960)))]; | |
| tensor<fp16, [512]> var_357_to_fp16 = const()[name = string("op_357_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18069312)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_15_cast_fp16 = linear(bias = var_357_to_fp16, weight = var_356_to_fp16, x = x_35_cast_fp16)[name = string("linear_15_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_37_cast_fp16 = add(x = x_31_cast_fp16, y = linear_15_cast_fp16)[name = string("x_37_cast_fp16")]; | |
| tensor<int32, [1]> var_364_axes_0 = const()[name = string("op_364_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_2_mlp_ln_weight_to_fp16 = const()[name = string("blocks_2_mlp_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18070400)))]; | |
| tensor<fp16, [512]> blocks_2_mlp_ln_bias_to_fp16 = const()[name = string("blocks_2_mlp_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18071488)))]; | |
| tensor<fp16, [1, 1500, 512]> var_364_cast_fp16 = layer_norm(axes = var_364_axes_0, beta = blocks_2_mlp_ln_bias_to_fp16, epsilon = var_290_to_fp16, gamma = blocks_2_mlp_ln_weight_to_fp16, x = x_37_cast_fp16)[name = string("op_364_cast_fp16")]; | |
| tensor<fp16, [2048, 512]> var_373_to_fp16 = const()[name = string("op_373_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18072576)))]; | |
| tensor<fp16, [2048]> var_374_to_fp16 = const()[name = string("op_374_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20169792)))]; | |
| tensor<fp16, [1, 1500, 2048]> linear_16_cast_fp16 = linear(bias = var_374_to_fp16, weight = var_373_to_fp16, x = var_364_cast_fp16)[name = string("linear_16_cast_fp16")]; | |
| string x_41_mode_0 = const()[name = string("x_41_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 1500, 2048]> x_41_cast_fp16 = gelu(mode = x_41_mode_0, x = linear_16_cast_fp16)[name = string("x_41_cast_fp16")]; | |
| tensor<fp16, [512, 2048]> var_379_to_fp16 = const()[name = string("op_379_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20173952)))]; | |
| tensor<fp16, [512]> var_380_to_fp16 = const()[name = string("op_380_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22271168)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_17_cast_fp16 = linear(bias = var_380_to_fp16, weight = var_379_to_fp16, x = x_41_cast_fp16)[name = string("linear_17_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_43_cast_fp16 = add(x = x_37_cast_fp16, y = linear_17_cast_fp16)[name = string("x_43_cast_fp16")]; | |
| int32 var_390 = const()[name = string("op_390"), val = int32(-1)]; | |
| tensor<int32, [1]> var_406_axes_0 = const()[name = string("op_406_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_3_attn_ln_weight_to_fp16 = const()[name = string("blocks_3_attn_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22272256)))]; | |
| tensor<fp16, [512]> blocks_3_attn_ln_bias_to_fp16 = const()[name = string("blocks_3_attn_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22273344)))]; | |
| fp16 var_396_to_fp16 = const()[name = string("op_396_to_fp16"), val = fp16(0x1.5p-17)]; | |
| tensor<fp16, [1, 1500, 512]> var_406_cast_fp16 = layer_norm(axes = var_406_axes_0, beta = blocks_3_attn_ln_bias_to_fp16, epsilon = var_396_to_fp16, gamma = blocks_3_attn_ln_weight_to_fp16, x = x_43_cast_fp16)[name = string("op_406_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_417_to_fp16 = const()[name = string("op_417_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22274432)))]; | |
| tensor<fp16, [512]> var_418_to_fp16 = const()[name = string("op_418_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22798784)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_18_cast_fp16 = linear(bias = var_418_to_fp16, weight = var_417_to_fp16, x = var_406_cast_fp16)[name = string("linear_18_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_421_to_fp16 = const()[name = string("op_421_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22799872)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_19_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_421_to_fp16, x = var_406_cast_fp16)[name = string("linear_19_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_425_to_fp16 = const()[name = string("op_425_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23324224)))]; | |
| tensor<fp16, [512]> var_426_to_fp16 = const()[name = string("op_426_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23848576)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_20_cast_fp16 = linear(bias = var_426_to_fp16, weight = var_425_to_fp16, x = var_406_cast_fp16)[name = string("linear_20_cast_fp16")]; | |
| tensor<int32, [4]> var_434 = const()[name = string("op_434"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_435_cast_fp16 = reshape(shape = var_434, x = linear_18_cast_fp16)[name = string("op_435_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_48_to_fp16 = const()[name = string("const_48_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> q_15_cast_fp16 = mul(x = var_435_cast_fp16, y = const_48_to_fp16)[name = string("q_15_cast_fp16")]; | |
| tensor<int32, [4]> var_441 = const()[name = string("op_441"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_442_cast_fp16 = reshape(shape = var_441, x = linear_19_cast_fp16)[name = string("op_442_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_49_to_fp16 = const()[name = string("const_49_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> k_15_cast_fp16 = mul(x = var_442_cast_fp16, y = const_49_to_fp16)[name = string("k_15_cast_fp16")]; | |
| tensor<int32, [4]> var_448 = const()[name = string("op_448"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_449_cast_fp16 = reshape(shape = var_448, x = linear_20_cast_fp16)[name = string("op_449_cast_fp16")]; | |
| tensor<int32, [4]> var_450 = const()[name = string("op_450"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| bool qk_7_transpose_x_0 = const()[name = string("qk_7_transpose_x_0"), val = bool(false)]; | |
| bool qk_7_transpose_y_0 = const()[name = string("qk_7_transpose_y_0"), val = bool(false)]; | |
| tensor<int32, [4]> transpose_30_perm_0 = const()[name = string("transpose_30_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; | |
| tensor<int32, [4]> transpose_31_perm_0 = const()[name = string("transpose_31_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])]; | |
| tensor<fp16, [1, 8, 64, 1500]> transpose_31 = transpose(perm = transpose_31_perm_0, x = k_15_cast_fp16)[name = string("transpose_45")]; | |
| tensor<fp16, [1, 8, 1500, 64]> transpose_30 = transpose(perm = transpose_30_perm_0, x = q_15_cast_fp16)[name = string("transpose_46")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> qk_7_cast_fp16 = matmul(transpose_x = qk_7_transpose_x_0, transpose_y = qk_7_transpose_y_0, x = transpose_30, y = transpose_31)[name = string("qk_7_cast_fp16")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> var_454_cast_fp16 = softmax(axis = var_390, x = qk_7_cast_fp16)[name = string("op_454_cast_fp16")]; | |
| bool var_456_transpose_x_0 = const()[name = string("op_456_transpose_x_0"), val = bool(false)]; | |
| bool var_456_transpose_y_0 = const()[name = string("op_456_transpose_y_0"), val = bool(false)]; | |
| tensor<fp16, [1, 8, 1500, 64]> v_15_cast_fp16 = transpose(perm = var_450, x = var_449_cast_fp16)[name = string("transpose_47")]; | |
| tensor<fp16, [1, 8, 1500, 64]> var_456_cast_fp16 = matmul(transpose_x = var_456_transpose_x_0, transpose_y = var_456_transpose_y_0, x = var_454_cast_fp16, y = v_15_cast_fp16)[name = string("op_456_cast_fp16")]; | |
| tensor<int32, [4]> var_457 = const()[name = string("op_457"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| tensor<int32, [3]> concat_3 = const()[name = string("concat_3"), val = tensor<int32, [3]>([1, 1500, 512])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_458_cast_fp16 = transpose(perm = var_457, x = var_456_cast_fp16)[name = string("transpose_44")]; | |
| tensor<fp16, [1, 1500, 512]> x_47_cast_fp16 = reshape(shape = concat_3, x = var_458_cast_fp16)[name = string("x_47_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_462_to_fp16 = const()[name = string("op_462_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23849664)))]; | |
| tensor<fp16, [512]> var_463_to_fp16 = const()[name = string("op_463_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24374016)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_21_cast_fp16 = linear(bias = var_463_to_fp16, weight = var_462_to_fp16, x = x_47_cast_fp16)[name = string("linear_21_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_49_cast_fp16 = add(x = x_43_cast_fp16, y = linear_21_cast_fp16)[name = string("x_49_cast_fp16")]; | |
| tensor<int32, [1]> var_470_axes_0 = const()[name = string("op_470_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_3_mlp_ln_weight_to_fp16 = const()[name = string("blocks_3_mlp_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24375104)))]; | |
| tensor<fp16, [512]> blocks_3_mlp_ln_bias_to_fp16 = const()[name = string("blocks_3_mlp_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24376192)))]; | |
| tensor<fp16, [1, 1500, 512]> var_470_cast_fp16 = layer_norm(axes = var_470_axes_0, beta = blocks_3_mlp_ln_bias_to_fp16, epsilon = var_396_to_fp16, gamma = blocks_3_mlp_ln_weight_to_fp16, x = x_49_cast_fp16)[name = string("op_470_cast_fp16")]; | |
| tensor<fp16, [2048, 512]> var_479_to_fp16 = const()[name = string("op_479_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24377280)))]; | |
| tensor<fp16, [2048]> var_480_to_fp16 = const()[name = string("op_480_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26474496)))]; | |
| tensor<fp16, [1, 1500, 2048]> linear_22_cast_fp16 = linear(bias = var_480_to_fp16, weight = var_479_to_fp16, x = var_470_cast_fp16)[name = string("linear_22_cast_fp16")]; | |
| string x_53_mode_0 = const()[name = string("x_53_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 1500, 2048]> x_53_cast_fp16 = gelu(mode = x_53_mode_0, x = linear_22_cast_fp16)[name = string("x_53_cast_fp16")]; | |
| tensor<fp16, [512, 2048]> var_485_to_fp16 = const()[name = string("op_485_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26478656)))]; | |
| tensor<fp16, [512]> var_486_to_fp16 = const()[name = string("op_486_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28575872)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_23_cast_fp16 = linear(bias = var_486_to_fp16, weight = var_485_to_fp16, x = x_53_cast_fp16)[name = string("linear_23_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_55_cast_fp16 = add(x = x_49_cast_fp16, y = linear_23_cast_fp16)[name = string("x_55_cast_fp16")]; | |
| int32 var_496 = const()[name = string("op_496"), val = int32(-1)]; | |
| tensor<int32, [1]> var_512_axes_0 = const()[name = string("op_512_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_4_attn_ln_weight_to_fp16 = const()[name = string("blocks_4_attn_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28576960)))]; | |
| tensor<fp16, [512]> blocks_4_attn_ln_bias_to_fp16 = const()[name = string("blocks_4_attn_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28578048)))]; | |
| fp16 var_502_to_fp16 = const()[name = string("op_502_to_fp16"), val = fp16(0x1.5p-17)]; | |
| tensor<fp16, [1, 1500, 512]> var_512_cast_fp16 = layer_norm(axes = var_512_axes_0, beta = blocks_4_attn_ln_bias_to_fp16, epsilon = var_502_to_fp16, gamma = blocks_4_attn_ln_weight_to_fp16, x = x_55_cast_fp16)[name = string("op_512_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_523_to_fp16 = const()[name = string("op_523_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28579136)))]; | |
| tensor<fp16, [512]> var_524_to_fp16 = const()[name = string("op_524_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29103488)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_24_cast_fp16 = linear(bias = var_524_to_fp16, weight = var_523_to_fp16, x = var_512_cast_fp16)[name = string("linear_24_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_527_to_fp16 = const()[name = string("op_527_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29104576)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_25_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_527_to_fp16, x = var_512_cast_fp16)[name = string("linear_25_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_531_to_fp16 = const()[name = string("op_531_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29628928)))]; | |
| tensor<fp16, [512]> var_532_to_fp16 = const()[name = string("op_532_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30153280)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_26_cast_fp16 = linear(bias = var_532_to_fp16, weight = var_531_to_fp16, x = var_512_cast_fp16)[name = string("linear_26_cast_fp16")]; | |
| tensor<int32, [4]> var_540 = const()[name = string("op_540"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_541_cast_fp16 = reshape(shape = var_540, x = linear_24_cast_fp16)[name = string("op_541_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_50_to_fp16 = const()[name = string("const_50_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> q_19_cast_fp16 = mul(x = var_541_cast_fp16, y = const_50_to_fp16)[name = string("q_19_cast_fp16")]; | |
| tensor<int32, [4]> var_547 = const()[name = string("op_547"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_548_cast_fp16 = reshape(shape = var_547, x = linear_25_cast_fp16)[name = string("op_548_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> k_19_cast_fp16 = mul(x = var_548_cast_fp16, y = const_51_to_fp16)[name = string("k_19_cast_fp16")]; | |
| tensor<int32, [4]> var_554 = const()[name = string("op_554"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_555_cast_fp16 = reshape(shape = var_554, x = linear_26_cast_fp16)[name = string("op_555_cast_fp16")]; | |
| tensor<int32, [4]> var_556 = const()[name = string("op_556"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| bool qk_9_transpose_x_0 = const()[name = string("qk_9_transpose_x_0"), val = bool(false)]; | |
| bool qk_9_transpose_y_0 = const()[name = string("qk_9_transpose_y_0"), val = bool(false)]; | |
| tensor<int32, [4]> transpose_32_perm_0 = const()[name = string("transpose_32_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; | |
| tensor<int32, [4]> transpose_33_perm_0 = const()[name = string("transpose_33_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])]; | |
| tensor<fp16, [1, 8, 64, 1500]> transpose_33 = transpose(perm = transpose_33_perm_0, x = k_19_cast_fp16)[name = string("transpose_41")]; | |
| tensor<fp16, [1, 8, 1500, 64]> transpose_32 = transpose(perm = transpose_32_perm_0, x = q_19_cast_fp16)[name = string("transpose_42")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> qk_9_cast_fp16 = matmul(transpose_x = qk_9_transpose_x_0, transpose_y = qk_9_transpose_y_0, x = transpose_32, y = transpose_33)[name = string("qk_9_cast_fp16")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> var_560_cast_fp16 = softmax(axis = var_496, x = qk_9_cast_fp16)[name = string("op_560_cast_fp16")]; | |
| bool var_562_transpose_x_0 = const()[name = string("op_562_transpose_x_0"), val = bool(false)]; | |
| bool var_562_transpose_y_0 = const()[name = string("op_562_transpose_y_0"), val = bool(false)]; | |
| tensor<fp16, [1, 8, 1500, 64]> v_19_cast_fp16 = transpose(perm = var_556, x = var_555_cast_fp16)[name = string("transpose_43")]; | |
| tensor<fp16, [1, 8, 1500, 64]> var_562_cast_fp16 = matmul(transpose_x = var_562_transpose_x_0, transpose_y = var_562_transpose_y_0, x = var_560_cast_fp16, y = v_19_cast_fp16)[name = string("op_562_cast_fp16")]; | |
| tensor<int32, [4]> var_563 = const()[name = string("op_563"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| tensor<int32, [3]> concat_4 = const()[name = string("concat_4"), val = tensor<int32, [3]>([1, 1500, 512])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_564_cast_fp16 = transpose(perm = var_563, x = var_562_cast_fp16)[name = string("transpose_40")]; | |
| tensor<fp16, [1, 1500, 512]> x_59_cast_fp16 = reshape(shape = concat_4, x = var_564_cast_fp16)[name = string("x_59_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_568_to_fp16 = const()[name = string("op_568_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30154368)))]; | |
| tensor<fp16, [512]> var_569_to_fp16 = const()[name = string("op_569_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30678720)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_27_cast_fp16 = linear(bias = var_569_to_fp16, weight = var_568_to_fp16, x = x_59_cast_fp16)[name = string("linear_27_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_61_cast_fp16 = add(x = x_55_cast_fp16, y = linear_27_cast_fp16)[name = string("x_61_cast_fp16")]; | |
| tensor<int32, [1]> var_576_axes_0 = const()[name = string("op_576_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_4_mlp_ln_weight_to_fp16 = const()[name = string("blocks_4_mlp_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30679808)))]; | |
| tensor<fp16, [512]> blocks_4_mlp_ln_bias_to_fp16 = const()[name = string("blocks_4_mlp_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30680896)))]; | |
| tensor<fp16, [1, 1500, 512]> var_576_cast_fp16 = layer_norm(axes = var_576_axes_0, beta = blocks_4_mlp_ln_bias_to_fp16, epsilon = var_502_to_fp16, gamma = blocks_4_mlp_ln_weight_to_fp16, x = x_61_cast_fp16)[name = string("op_576_cast_fp16")]; | |
| tensor<fp16, [2048, 512]> var_585_to_fp16 = const()[name = string("op_585_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30681984)))]; | |
| tensor<fp16, [2048]> var_586_to_fp16 = const()[name = string("op_586_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32779200)))]; | |
| tensor<fp16, [1, 1500, 2048]> linear_28_cast_fp16 = linear(bias = var_586_to_fp16, weight = var_585_to_fp16, x = var_576_cast_fp16)[name = string("linear_28_cast_fp16")]; | |
| string x_65_mode_0 = const()[name = string("x_65_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 1500, 2048]> x_65_cast_fp16 = gelu(mode = x_65_mode_0, x = linear_28_cast_fp16)[name = string("x_65_cast_fp16")]; | |
| tensor<fp16, [512, 2048]> var_591_to_fp16 = const()[name = string("op_591_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32783360)))]; | |
| tensor<fp16, [512]> var_592_to_fp16 = const()[name = string("op_592_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34880576)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_29_cast_fp16 = linear(bias = var_592_to_fp16, weight = var_591_to_fp16, x = x_65_cast_fp16)[name = string("linear_29_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_67_cast_fp16 = add(x = x_61_cast_fp16, y = linear_29_cast_fp16)[name = string("x_67_cast_fp16")]; | |
| int32 var_602 = const()[name = string("op_602"), val = int32(-1)]; | |
| tensor<int32, [1]> var_618_axes_0 = const()[name = string("op_618_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_5_attn_ln_weight_to_fp16 = const()[name = string("blocks_5_attn_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34881664)))]; | |
| tensor<fp16, [512]> blocks_5_attn_ln_bias_to_fp16 = const()[name = string("blocks_5_attn_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34882752)))]; | |
| fp16 var_608_to_fp16 = const()[name = string("op_608_to_fp16"), val = fp16(0x1.5p-17)]; | |
| tensor<fp16, [1, 1500, 512]> var_618_cast_fp16 = layer_norm(axes = var_618_axes_0, beta = blocks_5_attn_ln_bias_to_fp16, epsilon = var_608_to_fp16, gamma = blocks_5_attn_ln_weight_to_fp16, x = x_67_cast_fp16)[name = string("op_618_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_629_to_fp16 = const()[name = string("op_629_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34883840)))]; | |
| tensor<fp16, [512]> var_630_to_fp16 = const()[name = string("op_630_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35408192)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_30_cast_fp16 = linear(bias = var_630_to_fp16, weight = var_629_to_fp16, x = var_618_cast_fp16)[name = string("linear_30_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_633_to_fp16 = const()[name = string("op_633_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35409280)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_31_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_633_to_fp16, x = var_618_cast_fp16)[name = string("linear_31_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_637_to_fp16 = const()[name = string("op_637_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35933632)))]; | |
| tensor<fp16, [512]> var_638_to_fp16 = const()[name = string("op_638_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36457984)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_32_cast_fp16 = linear(bias = var_638_to_fp16, weight = var_637_to_fp16, x = var_618_cast_fp16)[name = string("linear_32_cast_fp16")]; | |
| tensor<int32, [4]> var_646 = const()[name = string("op_646"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_647_cast_fp16 = reshape(shape = var_646, x = linear_30_cast_fp16)[name = string("op_647_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> q_cast_fp16 = mul(x = var_647_cast_fp16, y = const_52_to_fp16)[name = string("q_cast_fp16")]; | |
| tensor<int32, [4]> var_653 = const()[name = string("op_653"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_654_cast_fp16 = reshape(shape = var_653, x = linear_31_cast_fp16)[name = string("op_654_cast_fp16")]; | |
| tensor<fp16, [1, 1, 1, 1]> const_53_to_fp16 = const()[name = string("const_53_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])]; | |
| tensor<fp16, [1, 1500, 8, 64]> k_cast_fp16 = mul(x = var_654_cast_fp16, y = const_53_to_fp16)[name = string("k_cast_fp16")]; | |
| tensor<int32, [4]> var_660 = const()[name = string("op_660"), val = tensor<int32, [4]>([1, 1500, 8, -1])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_661_cast_fp16 = reshape(shape = var_660, x = linear_32_cast_fp16)[name = string("op_661_cast_fp16")]; | |
| tensor<int32, [4]> var_662 = const()[name = string("op_662"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| bool qk_transpose_x_0 = const()[name = string("qk_transpose_x_0"), val = bool(false)]; | |
| bool qk_transpose_y_0 = const()[name = string("qk_transpose_y_0"), val = bool(false)]; | |
| tensor<int32, [4]> transpose_34_perm_0 = const()[name = string("transpose_34_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; | |
| tensor<int32, [4]> transpose_35_perm_0 = const()[name = string("transpose_35_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])]; | |
| tensor<fp16, [1, 8, 64, 1500]> transpose_35 = transpose(perm = transpose_35_perm_0, x = k_cast_fp16)[name = string("transpose_37")]; | |
| tensor<fp16, [1, 8, 1500, 64]> transpose_34 = transpose(perm = transpose_34_perm_0, x = q_cast_fp16)[name = string("transpose_38")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> qk_cast_fp16 = matmul(transpose_x = qk_transpose_x_0, transpose_y = qk_transpose_y_0, x = transpose_34, y = transpose_35)[name = string("qk_cast_fp16")]; | |
| tensor<fp16, [1, 8, 1500, 1500]> var_666_cast_fp16 = softmax(axis = var_602, x = qk_cast_fp16)[name = string("op_666_cast_fp16")]; | |
| bool var_668_transpose_x_0 = const()[name = string("op_668_transpose_x_0"), val = bool(false)]; | |
| bool var_668_transpose_y_0 = const()[name = string("op_668_transpose_y_0"), val = bool(false)]; | |
| tensor<fp16, [1, 8, 1500, 64]> v_cast_fp16 = transpose(perm = var_662, x = var_661_cast_fp16)[name = string("transpose_39")]; | |
| tensor<fp16, [1, 8, 1500, 64]> var_668_cast_fp16 = matmul(transpose_x = var_668_transpose_x_0, transpose_y = var_668_transpose_y_0, x = var_666_cast_fp16, y = v_cast_fp16)[name = string("op_668_cast_fp16")]; | |
| tensor<int32, [4]> var_669 = const()[name = string("op_669"), val = tensor<int32, [4]>([0, 2, 1, 3])]; | |
| tensor<int32, [3]> concat_5 = const()[name = string("concat_5"), val = tensor<int32, [3]>([1, 1500, 512])]; | |
| tensor<fp16, [1, 1500, 8, 64]> var_670_cast_fp16 = transpose(perm = var_669, x = var_668_cast_fp16)[name = string("transpose_36")]; | |
| tensor<fp16, [1, 1500, 512]> x_71_cast_fp16 = reshape(shape = concat_5, x = var_670_cast_fp16)[name = string("x_71_cast_fp16")]; | |
| tensor<fp16, [512, 512]> var_674_to_fp16 = const()[name = string("op_674_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36459072)))]; | |
| tensor<fp16, [512]> var_675_to_fp16 = const()[name = string("op_675_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36983424)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_33_cast_fp16 = linear(bias = var_675_to_fp16, weight = var_674_to_fp16, x = x_71_cast_fp16)[name = string("linear_33_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_73_cast_fp16 = add(x = x_67_cast_fp16, y = linear_33_cast_fp16)[name = string("x_73_cast_fp16")]; | |
| tensor<int32, [1]> var_682_axes_0 = const()[name = string("op_682_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> blocks_5_mlp_ln_weight_to_fp16 = const()[name = string("blocks_5_mlp_ln_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36984512)))]; | |
| tensor<fp16, [512]> blocks_5_mlp_ln_bias_to_fp16 = const()[name = string("blocks_5_mlp_ln_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36985600)))]; | |
| tensor<fp16, [1, 1500, 512]> var_682_cast_fp16 = layer_norm(axes = var_682_axes_0, beta = blocks_5_mlp_ln_bias_to_fp16, epsilon = var_608_to_fp16, gamma = blocks_5_mlp_ln_weight_to_fp16, x = x_73_cast_fp16)[name = string("op_682_cast_fp16")]; | |
| tensor<fp16, [2048, 512]> var_691_to_fp16 = const()[name = string("op_691_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36986688)))]; | |
| tensor<fp16, [2048]> var_692_to_fp16 = const()[name = string("op_692_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39083904)))]; | |
| tensor<fp16, [1, 1500, 2048]> linear_34_cast_fp16 = linear(bias = var_692_to_fp16, weight = var_691_to_fp16, x = var_682_cast_fp16)[name = string("linear_34_cast_fp16")]; | |
| string x_77_mode_0 = const()[name = string("x_77_mode_0"), val = string("EXACT")]; | |
| tensor<fp16, [1, 1500, 2048]> x_77_cast_fp16 = gelu(mode = x_77_mode_0, x = linear_34_cast_fp16)[name = string("x_77_cast_fp16")]; | |
| tensor<fp16, [512, 2048]> var_697_to_fp16 = const()[name = string("op_697_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39088064)))]; | |
| tensor<fp16, [512]> var_698_to_fp16 = const()[name = string("op_698_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41185280)))]; | |
| tensor<fp16, [1, 1500, 512]> linear_35_cast_fp16 = linear(bias = var_698_to_fp16, weight = var_697_to_fp16, x = x_77_cast_fp16)[name = string("linear_35_cast_fp16")]; | |
| tensor<fp16, [1, 1500, 512]> x_cast_fp16 = add(x = x_73_cast_fp16, y = linear_35_cast_fp16)[name = string("x_cast_fp16")]; | |
| tensor<int32, [1]> var_711_axes_0 = const()[name = string("op_711_axes_0"), val = tensor<int32, [1]>([-1])]; | |
| tensor<fp16, [512]> ln_post_weight_to_fp16 = const()[name = string("ln_post_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41186368)))]; | |
| tensor<fp16, [512]> ln_post_bias_to_fp16 = const()[name = string("ln_post_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41187456)))]; | |
| fp16 var_702_to_fp16 = const()[name = string("op_702_to_fp16"), val = fp16(0x1.5p-17)]; | |
| tensor<fp16, [1, 1500, 512]> output = layer_norm(axes = var_711_axes_0, beta = ln_post_bias_to_fp16, epsilon = var_702_to_fp16, gamma = ln_post_weight_to_fp16, x = x_cast_fp16)[name = string("op_711_cast_fp16")]; | |
| } -> (output); | |
| } |