| 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, ?, 384]> audio_data, state<tensor<fp16, [4, 1, 448, 384]>> k_cache1, state<tensor<fp16, [4, 1, 1500, 384]>> k_cache2, state<tensor<fp16, [4, 1, 448, 384]>> v_cache1, state<tensor<fp16, [4, 1, 1500, 384]>> v_cache2) [FlexibleShapeInformation = tuple<tuple<string, dict<string, tensor<int32, [?]>>>, tuple<string, dict<string, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"audio_data", [1, 1, 384]}}), ("RangeDims", {{"audio_data", [[1, 1], [1, 1500], [384, 384]]}})))] { | |
| tensor<fp16, [1, ?, 384]> dummy = identity(x = audio_data)[name = string("identity_0")]; | |
| tensor<fp16, [4, 1, 448, 384]> read_state_0 = read_state(input = k_cache1)[name = string("read_state_0")]; | |
| tensor<int32, [4]> concat_0 = const()[name = string("concat_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [4]> concat_1 = const()[name = string("concat_1"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [4]> k_cache1_internal_tensor_assign_1_stride_0 = const()[name = string("k_cache1_internal_tensor_assign_1_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> k_cache1_internal_tensor_assign_1_begin_mask_0 = const()[name = string("k_cache1_internal_tensor_assign_1_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> k_cache1_internal_tensor_assign_1_end_mask_0 = const()[name = string("k_cache1_internal_tensor_assign_1_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])]; | |
| tensor<bool, [4]> k_cache1_internal_tensor_assign_1_squeeze_mask_0 = const()[name = string("k_cache1_internal_tensor_assign_1_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<fp16, [4, 1, 448, 384]> const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = tensor<fp16, [4, 1, 448, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))]; | |
| tensor<fp16, [4, 1, 448, 384]> k_cache1_internal_tensor_assign_1_cast_fp16 = slice_update(begin = concat_0, begin_mask = k_cache1_internal_tensor_assign_1_begin_mask_0, end = concat_1, end_mask = k_cache1_internal_tensor_assign_1_end_mask_0, squeeze_mask = k_cache1_internal_tensor_assign_1_squeeze_mask_0, stride = k_cache1_internal_tensor_assign_1_stride_0, update = const_0_to_fp16, x = read_state_0)[name = string("k_cache1_internal_tensor_assign_1_cast_fp16")]; | |
| write_state(data = k_cache1_internal_tensor_assign_1_cast_fp16, input = k_cache1)[name = string("coreml_update_state_10_write_state")]; | |
| tensor<fp16, [4, 1, 448, 384]> read_state_1 = read_state(input = v_cache1)[name = string("read_state_1")]; | |
| tensor<int32, [4]> concat_2 = const()[name = string("concat_2"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [4]> concat_3 = const()[name = string("concat_3"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [4]> v_cache1_internal_tensor_assign_1_stride_0 = const()[name = string("v_cache1_internal_tensor_assign_1_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> v_cache1_internal_tensor_assign_1_begin_mask_0 = const()[name = string("v_cache1_internal_tensor_assign_1_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> v_cache1_internal_tensor_assign_1_end_mask_0 = const()[name = string("v_cache1_internal_tensor_assign_1_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])]; | |
| tensor<bool, [4]> v_cache1_internal_tensor_assign_1_squeeze_mask_0 = const()[name = string("v_cache1_internal_tensor_assign_1_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<fp16, [4, 1, 448, 384]> v_cache1_internal_tensor_assign_1_cast_fp16 = slice_update(begin = concat_2, begin_mask = v_cache1_internal_tensor_assign_1_begin_mask_0, end = concat_3, end_mask = v_cache1_internal_tensor_assign_1_end_mask_0, squeeze_mask = v_cache1_internal_tensor_assign_1_squeeze_mask_0, stride = v_cache1_internal_tensor_assign_1_stride_0, update = const_0_to_fp16, x = read_state_1)[name = string("v_cache1_internal_tensor_assign_1_cast_fp16")]; | |
| write_state(data = v_cache1_internal_tensor_assign_1_cast_fp16, input = v_cache1)[name = string("coreml_update_state_11_write_state")]; | |
| tensor<fp16, [4, 1, 1500, 384]> read_state_2 = read_state(input = k_cache2)[name = string("read_state_2")]; | |
| tensor<fp16, [4, 1, 1500, 384]> read_state_3 = read_state(input = v_cache2)[name = string("read_state_3")]; | |
| tensor<fp16, [384, 384]> var_75_to_fp16 = const()[name = string("op_75_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1376384)))]; | |
| tensor<fp16, [384]> linear_0_bias_0_to_fp16 = const()[name = string("linear_0_bias_0_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1671360)))]; | |
| tensor<fp16, [1, ?, 384]> linear_0_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = var_75_to_fp16, x = audio_data)[name = string("linear_0_cast_fp16")]; | |
| tensor<fp16, [384, 384]> var_79_to_fp16 = const()[name = string("op_79_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1672192)))]; | |
| tensor<fp16, [384]> var_80_to_fp16 = const()[name = string("op_80_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1967168)))]; | |
| tensor<fp16, [1, ?, 384]> linear_1_cast_fp16 = linear(bias = var_80_to_fp16, weight = var_79_to_fp16, x = audio_data)[name = string("linear_1_cast_fp16")]; | |
| tensor<int32, [3]> var_82_shape_cast_fp16 = shape(x = linear_0_cast_fp16)[name = string("op_82_shape_cast_fp16")]; | |
| int32 gather_0_axis_0 = const()[name = string("gather_0_axis_0"), val = int32(0)]; | |
| int32 gather_0_batch_dims_0 = const()[name = string("gather_0_batch_dims_0"), val = int32(0)]; | |
| bool gather_0_validate_indices_0 = const()[name = string("gather_0_validate_indices_0"), val = bool(false)]; | |
| string var_82_shape_cast_fp16_to_int16_dtype_0 = const()[name = string("op_82_shape_cast_fp16_to_int16_dtype_0"), val = string("int16")]; | |
| uint16 select_0_to_uint16 = const()[name = string("select_0_to_uint16"), val = uint16(1)]; | |
| tensor<int16, [3]> var_82_shape_cast_fp16_to_int16 = cast(dtype = var_82_shape_cast_fp16_to_int16_dtype_0, x = var_82_shape_cast_fp16)[name = string("cast_31")]; | |
| int16 gather_0_cast_uint16 = gather(axis = gather_0_axis_0, batch_dims = gather_0_batch_dims_0, indices = select_0_to_uint16, validate_indices = gather_0_validate_indices_0, x = var_82_shape_cast_fp16_to_int16)[name = string("gather_0_cast_uint16")]; | |
| string gather_0_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_0_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_11_axes_0 = const()[name = string("expand_dims_11_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_0_cast_uint16_to_int32 = cast(dtype = gather_0_cast_uint16_to_int32_dtype_0, x = gather_0_cast_uint16)[name = string("cast_30")]; | |
| tensor<int32, [1]> expand_dims_11 = expand_dims(axes = expand_dims_11_axes_0, x = gather_0_cast_uint16_to_int32)[name = string("expand_dims_11")]; | |
| tensor<int32, [4]> concat_5 = const()[name = string("concat_5"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_6_values0_0 = const()[name = string("concat_6_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_6_values1_0 = const()[name = string("concat_6_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_6_values3_0 = const()[name = string("concat_6_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_6_axis_0 = const()[name = string("concat_6_axis_0"), val = int32(0)]; | |
| bool concat_6_interleave_0 = const()[name = string("concat_6_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (concat_6_values0_0, concat_6_values1_0, expand_dims_11, concat_6_values3_0))[name = string("concat_6")]; | |
| tensor<int32, [4]> k_cache2_internal_tensor_assign_1_stride_0 = const()[name = string("k_cache2_internal_tensor_assign_1_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_1_begin_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_1_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_1_end_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_1_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_1_squeeze_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_1_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> k_cache2_internal_tensor_assign_1_cast_fp16 = slice_update(begin = concat_5, begin_mask = k_cache2_internal_tensor_assign_1_begin_mask_0, end = concat_6, end_mask = k_cache2_internal_tensor_assign_1_end_mask_0, squeeze_mask = k_cache2_internal_tensor_assign_1_squeeze_mask_0, stride = k_cache2_internal_tensor_assign_1_stride_0, update = linear_0_cast_fp16, x = read_state_2)[name = string("k_cache2_internal_tensor_assign_1_cast_fp16")]; | |
| write_state(data = k_cache2_internal_tensor_assign_1_cast_fp16, input = k_cache2)[name = string("coreml_update_state_12_write_state")]; | |
| tensor<fp16, [4, 1, 1500, 384]> coreml_update_state_12 = read_state(input = k_cache2)[name = string("coreml_update_state_12")]; | |
| tensor<int32, [3]> var_87_shape_cast_fp16 = shape(x = linear_1_cast_fp16)[name = string("op_87_shape_cast_fp16")]; | |
| int32 gather_1_axis_0 = const()[name = string("gather_1_axis_0"), val = int32(0)]; | |
| int32 gather_1_batch_dims_0 = const()[name = string("gather_1_batch_dims_0"), val = int32(0)]; | |
| bool gather_1_validate_indices_0 = const()[name = string("gather_1_validate_indices_0"), val = bool(false)]; | |
| string var_87_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_87_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")]; | |
| uint16 select_1_to_uint16 = const()[name = string("select_1_to_uint16"), val = uint16(1)]; | |
| tensor<uint16, [3]> var_87_shape_cast_fp16_to_uint16 = cast(dtype = var_87_shape_cast_fp16_to_uint16_dtype_0, x = var_87_shape_cast_fp16)[name = string("cast_29")]; | |
| uint16 gather_1_cast_uint16 = gather(axis = gather_1_axis_0, batch_dims = gather_1_batch_dims_0, indices = select_1_to_uint16, validate_indices = gather_1_validate_indices_0, x = var_87_shape_cast_fp16_to_uint16)[name = string("gather_1_cast_uint16")]; | |
| string gather_1_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_1_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_15_axes_0 = const()[name = string("expand_dims_15_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_1_cast_uint16_to_int32 = cast(dtype = gather_1_cast_uint16_to_int32_dtype_0, x = gather_1_cast_uint16)[name = string("cast_28")]; | |
| tensor<int32, [1]> expand_dims_15 = expand_dims(axes = expand_dims_15_axes_0, x = gather_1_cast_uint16_to_int32)[name = string("expand_dims_15")]; | |
| tensor<int32, [4]> concat_8 = const()[name = string("concat_8"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_9_values0_0 = const()[name = string("concat_9_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_9_values1_0 = const()[name = string("concat_9_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_9_values3_0 = const()[name = string("concat_9_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_9_axis_0 = const()[name = string("concat_9_axis_0"), val = int32(0)]; | |
| bool concat_9_interleave_0 = const()[name = string("concat_9_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (concat_9_values0_0, concat_9_values1_0, expand_dims_15, concat_9_values3_0))[name = string("concat_9")]; | |
| tensor<int32, [4]> v_cache2_internal_tensor_assign_1_stride_0 = const()[name = string("v_cache2_internal_tensor_assign_1_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_1_begin_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_1_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_1_end_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_1_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_1_squeeze_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_1_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> v_cache2_internal_tensor_assign_1_cast_fp16 = slice_update(begin = concat_8, begin_mask = v_cache2_internal_tensor_assign_1_begin_mask_0, end = concat_9, end_mask = v_cache2_internal_tensor_assign_1_end_mask_0, squeeze_mask = v_cache2_internal_tensor_assign_1_squeeze_mask_0, stride = v_cache2_internal_tensor_assign_1_stride_0, update = linear_1_cast_fp16, x = read_state_3)[name = string("v_cache2_internal_tensor_assign_1_cast_fp16")]; | |
| write_state(data = v_cache2_internal_tensor_assign_1_cast_fp16, input = v_cache2)[name = string("coreml_update_state_13_write_state")]; | |
| tensor<fp16, [4, 1, 1500, 384]> coreml_update_state_13 = read_state(input = v_cache2)[name = string("coreml_update_state_13")]; | |
| tensor<fp16, [384, 384]> var_109_to_fp16 = const()[name = string("op_109_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1968000)))]; | |
| tensor<fp16, [1, ?, 384]> linear_2_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = var_109_to_fp16, x = audio_data)[name = string("linear_2_cast_fp16")]; | |
| tensor<fp16, [384, 384]> var_113_to_fp16 = const()[name = string("op_113_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2262976)))]; | |
| tensor<fp16, [384]> var_114_to_fp16 = const()[name = string("op_114_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2557952)))]; | |
| tensor<fp16, [1, ?, 384]> linear_3_cast_fp16 = linear(bias = var_114_to_fp16, weight = var_113_to_fp16, x = audio_data)[name = string("linear_3_cast_fp16")]; | |
| tensor<int32, [3]> var_116_shape_cast_fp16 = shape(x = linear_2_cast_fp16)[name = string("op_116_shape_cast_fp16")]; | |
| int32 gather_2_axis_0 = const()[name = string("gather_2_axis_0"), val = int32(0)]; | |
| int32 gather_2_batch_dims_0 = const()[name = string("gather_2_batch_dims_0"), val = int32(0)]; | |
| bool gather_2_validate_indices_0 = const()[name = string("gather_2_validate_indices_0"), val = bool(false)]; | |
| string var_116_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_116_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")]; | |
| uint16 select_2_to_uint16 = const()[name = string("select_2_to_uint16"), val = uint16(1)]; | |
| tensor<uint16, [3]> var_116_shape_cast_fp16_to_uint16 = cast(dtype = var_116_shape_cast_fp16_to_uint16_dtype_0, x = var_116_shape_cast_fp16)[name = string("cast_27")]; | |
| uint16 gather_2_cast_uint16 = gather(axis = gather_2_axis_0, batch_dims = gather_2_batch_dims_0, indices = select_2_to_uint16, validate_indices = gather_2_validate_indices_0, x = var_116_shape_cast_fp16_to_uint16)[name = string("gather_2_cast_uint16")]; | |
| string gather_2_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_2_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_19_axes_0 = const()[name = string("expand_dims_19_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_2_cast_uint16_to_int32 = cast(dtype = gather_2_cast_uint16_to_int32_dtype_0, x = gather_2_cast_uint16)[name = string("cast_26")]; | |
| tensor<int32, [1]> expand_dims_19 = expand_dims(axes = expand_dims_19_axes_0, x = gather_2_cast_uint16_to_int32)[name = string("expand_dims_19")]; | |
| tensor<int32, [4]> concat_11 = const()[name = string("concat_11"), val = tensor<int32, [4]>([1, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_12_values0_0 = const()[name = string("concat_12_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_12_values1_0 = const()[name = string("concat_12_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_12_values3_0 = const()[name = string("concat_12_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_12_axis_0 = const()[name = string("concat_12_axis_0"), val = int32(0)]; | |
| bool concat_12_interleave_0 = const()[name = string("concat_12_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (concat_12_values0_0, concat_12_values1_0, expand_dims_19, concat_12_values3_0))[name = string("concat_12")]; | |
| tensor<int32, [4]> k_cache2_internal_tensor_assign_2_stride_0 = const()[name = string("k_cache2_internal_tensor_assign_2_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_2_begin_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_2_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_2_end_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_2_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_2_squeeze_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_2_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> k_cache2_internal_tensor_assign_2_cast_fp16 = slice_update(begin = concat_11, begin_mask = k_cache2_internal_tensor_assign_2_begin_mask_0, end = concat_12, end_mask = k_cache2_internal_tensor_assign_2_end_mask_0, squeeze_mask = k_cache2_internal_tensor_assign_2_squeeze_mask_0, stride = k_cache2_internal_tensor_assign_2_stride_0, update = linear_2_cast_fp16, x = coreml_update_state_12)[name = string("k_cache2_internal_tensor_assign_2_cast_fp16")]; | |
| write_state(data = k_cache2_internal_tensor_assign_2_cast_fp16, input = k_cache2)[name = string("coreml_update_state_14_write_state")]; | |
| tensor<fp16, [4, 1, 1500, 384]> coreml_update_state_14 = read_state(input = k_cache2)[name = string("coreml_update_state_14")]; | |
| tensor<int32, [3]> var_121_shape_cast_fp16 = shape(x = linear_3_cast_fp16)[name = string("op_121_shape_cast_fp16")]; | |
| int32 gather_3_axis_0 = const()[name = string("gather_3_axis_0"), val = int32(0)]; | |
| int32 gather_3_batch_dims_0 = const()[name = string("gather_3_batch_dims_0"), val = int32(0)]; | |
| bool gather_3_validate_indices_0 = const()[name = string("gather_3_validate_indices_0"), val = bool(false)]; | |
| string var_121_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_121_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")]; | |
| uint16 select_3_to_uint16 = const()[name = string("select_3_to_uint16"), val = uint16(1)]; | |
| tensor<uint16, [3]> var_121_shape_cast_fp16_to_uint16 = cast(dtype = var_121_shape_cast_fp16_to_uint16_dtype_0, x = var_121_shape_cast_fp16)[name = string("cast_25")]; | |
| uint16 gather_3_cast_uint16 = gather(axis = gather_3_axis_0, batch_dims = gather_3_batch_dims_0, indices = select_3_to_uint16, validate_indices = gather_3_validate_indices_0, x = var_121_shape_cast_fp16_to_uint16)[name = string("gather_3_cast_uint16")]; | |
| string gather_3_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_3_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_23_axes_0 = const()[name = string("expand_dims_23_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_3_cast_uint16_to_int32 = cast(dtype = gather_3_cast_uint16_to_int32_dtype_0, x = gather_3_cast_uint16)[name = string("cast_24")]; | |
| tensor<int32, [1]> expand_dims_23 = expand_dims(axes = expand_dims_23_axes_0, x = gather_3_cast_uint16_to_int32)[name = string("expand_dims_23")]; | |
| tensor<int32, [4]> concat_14 = const()[name = string("concat_14"), val = tensor<int32, [4]>([1, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_15_values0_0 = const()[name = string("concat_15_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_15_values1_0 = const()[name = string("concat_15_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_15_values3_0 = const()[name = string("concat_15_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_15_axis_0 = const()[name = string("concat_15_axis_0"), val = int32(0)]; | |
| bool concat_15_interleave_0 = const()[name = string("concat_15_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (concat_15_values0_0, concat_15_values1_0, expand_dims_23, concat_15_values3_0))[name = string("concat_15")]; | |
| tensor<int32, [4]> v_cache2_internal_tensor_assign_2_stride_0 = const()[name = string("v_cache2_internal_tensor_assign_2_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_2_begin_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_2_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_2_end_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_2_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_2_squeeze_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_2_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> v_cache2_internal_tensor_assign_2_cast_fp16 = slice_update(begin = concat_14, begin_mask = v_cache2_internal_tensor_assign_2_begin_mask_0, end = concat_15, end_mask = v_cache2_internal_tensor_assign_2_end_mask_0, squeeze_mask = v_cache2_internal_tensor_assign_2_squeeze_mask_0, stride = v_cache2_internal_tensor_assign_2_stride_0, update = linear_3_cast_fp16, x = coreml_update_state_13)[name = string("v_cache2_internal_tensor_assign_2_cast_fp16")]; | |
| write_state(data = v_cache2_internal_tensor_assign_2_cast_fp16, input = v_cache2)[name = string("coreml_update_state_15_write_state")]; | |
| tensor<fp16, [4, 1, 1500, 384]> coreml_update_state_15 = read_state(input = v_cache2)[name = string("coreml_update_state_15")]; | |
| tensor<fp16, [384, 384]> var_143_to_fp16 = const()[name = string("op_143_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2558784)))]; | |
| tensor<fp16, [1, ?, 384]> linear_4_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = var_143_to_fp16, x = audio_data)[name = string("linear_4_cast_fp16")]; | |
| tensor<fp16, [384, 384]> var_147_to_fp16 = const()[name = string("op_147_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2853760)))]; | |
| tensor<fp16, [384]> var_148_to_fp16 = const()[name = string("op_148_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3148736)))]; | |
| tensor<fp16, [1, ?, 384]> linear_5_cast_fp16 = linear(bias = var_148_to_fp16, weight = var_147_to_fp16, x = audio_data)[name = string("linear_5_cast_fp16")]; | |
| tensor<int32, [3]> var_150_shape_cast_fp16 = shape(x = linear_4_cast_fp16)[name = string("op_150_shape_cast_fp16")]; | |
| int32 gather_4_axis_0 = const()[name = string("gather_4_axis_0"), val = int32(0)]; | |
| int32 gather_4_batch_dims_0 = const()[name = string("gather_4_batch_dims_0"), val = int32(0)]; | |
| bool gather_4_validate_indices_0 = const()[name = string("gather_4_validate_indices_0"), val = bool(false)]; | |
| string var_150_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_150_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")]; | |
| uint16 select_4_to_uint16 = const()[name = string("select_4_to_uint16"), val = uint16(1)]; | |
| tensor<uint16, [3]> var_150_shape_cast_fp16_to_uint16 = cast(dtype = var_150_shape_cast_fp16_to_uint16_dtype_0, x = var_150_shape_cast_fp16)[name = string("cast_23")]; | |
| uint16 gather_4_cast_uint16 = gather(axis = gather_4_axis_0, batch_dims = gather_4_batch_dims_0, indices = select_4_to_uint16, validate_indices = gather_4_validate_indices_0, x = var_150_shape_cast_fp16_to_uint16)[name = string("gather_4_cast_uint16")]; | |
| string gather_4_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_4_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_27_axes_0 = const()[name = string("expand_dims_27_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_4_cast_uint16_to_int32 = cast(dtype = gather_4_cast_uint16_to_int32_dtype_0, x = gather_4_cast_uint16)[name = string("cast_22")]; | |
| tensor<int32, [1]> expand_dims_27 = expand_dims(axes = expand_dims_27_axes_0, x = gather_4_cast_uint16_to_int32)[name = string("expand_dims_27")]; | |
| tensor<int32, [4]> concat_17 = const()[name = string("concat_17"), val = tensor<int32, [4]>([2, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_18_values0_0 = const()[name = string("concat_18_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_18_values1_0 = const()[name = string("concat_18_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_18_values3_0 = const()[name = string("concat_18_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_18_axis_0 = const()[name = string("concat_18_axis_0"), val = int32(0)]; | |
| bool concat_18_interleave_0 = const()[name = string("concat_18_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (concat_18_values0_0, concat_18_values1_0, expand_dims_27, concat_18_values3_0))[name = string("concat_18")]; | |
| tensor<int32, [4]> k_cache2_internal_tensor_assign_3_stride_0 = const()[name = string("k_cache2_internal_tensor_assign_3_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_3_begin_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_3_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_3_end_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_3_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_3_squeeze_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_3_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> k_cache2_internal_tensor_assign_3_cast_fp16 = slice_update(begin = concat_17, begin_mask = k_cache2_internal_tensor_assign_3_begin_mask_0, end = concat_18, end_mask = k_cache2_internal_tensor_assign_3_end_mask_0, squeeze_mask = k_cache2_internal_tensor_assign_3_squeeze_mask_0, stride = k_cache2_internal_tensor_assign_3_stride_0, update = linear_4_cast_fp16, x = coreml_update_state_14)[name = string("k_cache2_internal_tensor_assign_3_cast_fp16")]; | |
| write_state(data = k_cache2_internal_tensor_assign_3_cast_fp16, input = k_cache2)[name = string("coreml_update_state_16_write_state")]; | |
| tensor<fp16, [4, 1, 1500, 384]> coreml_update_state_16 = read_state(input = k_cache2)[name = string("coreml_update_state_16")]; | |
| tensor<int32, [3]> var_155_shape_cast_fp16 = shape(x = linear_5_cast_fp16)[name = string("op_155_shape_cast_fp16")]; | |
| int32 gather_5_axis_0 = const()[name = string("gather_5_axis_0"), val = int32(0)]; | |
| int32 gather_5_batch_dims_0 = const()[name = string("gather_5_batch_dims_0"), val = int32(0)]; | |
| bool gather_5_validate_indices_0 = const()[name = string("gather_5_validate_indices_0"), val = bool(false)]; | |
| string var_155_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_155_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")]; | |
| uint16 select_5_to_uint16 = const()[name = string("select_5_to_uint16"), val = uint16(1)]; | |
| tensor<uint16, [3]> var_155_shape_cast_fp16_to_uint16 = cast(dtype = var_155_shape_cast_fp16_to_uint16_dtype_0, x = var_155_shape_cast_fp16)[name = string("cast_21")]; | |
| uint16 gather_5_cast_uint16 = gather(axis = gather_5_axis_0, batch_dims = gather_5_batch_dims_0, indices = select_5_to_uint16, validate_indices = gather_5_validate_indices_0, x = var_155_shape_cast_fp16_to_uint16)[name = string("gather_5_cast_uint16")]; | |
| string gather_5_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_5_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_31_axes_0 = const()[name = string("expand_dims_31_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_5_cast_uint16_to_int32 = cast(dtype = gather_5_cast_uint16_to_int32_dtype_0, x = gather_5_cast_uint16)[name = string("cast_20")]; | |
| tensor<int32, [1]> expand_dims_31 = expand_dims(axes = expand_dims_31_axes_0, x = gather_5_cast_uint16_to_int32)[name = string("expand_dims_31")]; | |
| tensor<int32, [4]> concat_20 = const()[name = string("concat_20"), val = tensor<int32, [4]>([2, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_21_values0_0 = const()[name = string("concat_21_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_21_values1_0 = const()[name = string("concat_21_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_21_values3_0 = const()[name = string("concat_21_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_21_axis_0 = const()[name = string("concat_21_axis_0"), val = int32(0)]; | |
| bool concat_21_interleave_0 = const()[name = string("concat_21_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (concat_21_values0_0, concat_21_values1_0, expand_dims_31, concat_21_values3_0))[name = string("concat_21")]; | |
| tensor<int32, [4]> v_cache2_internal_tensor_assign_3_stride_0 = const()[name = string("v_cache2_internal_tensor_assign_3_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_3_begin_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_3_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_3_end_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_3_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_3_squeeze_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_3_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> v_cache2_internal_tensor_assign_3_cast_fp16 = slice_update(begin = concat_20, begin_mask = v_cache2_internal_tensor_assign_3_begin_mask_0, end = concat_21, end_mask = v_cache2_internal_tensor_assign_3_end_mask_0, squeeze_mask = v_cache2_internal_tensor_assign_3_squeeze_mask_0, stride = v_cache2_internal_tensor_assign_3_stride_0, update = linear_5_cast_fp16, x = coreml_update_state_15)[name = string("v_cache2_internal_tensor_assign_3_cast_fp16")]; | |
| write_state(data = v_cache2_internal_tensor_assign_3_cast_fp16, input = v_cache2)[name = string("coreml_update_state_17_write_state")]; | |
| tensor<fp16, [4, 1, 1500, 384]> coreml_update_state_17 = read_state(input = v_cache2)[name = string("coreml_update_state_17")]; | |
| tensor<fp16, [384, 384]> var_177_to_fp16 = const()[name = string("op_177_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3149568)))]; | |
| tensor<fp16, [1, ?, 384]> linear_6_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = var_177_to_fp16, x = audio_data)[name = string("linear_6_cast_fp16")]; | |
| tensor<fp16, [384, 384]> var_181_to_fp16 = const()[name = string("op_181_to_fp16"), val = tensor<fp16, [384, 384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3444544)))]; | |
| tensor<fp16, [384]> var_182_to_fp16 = const()[name = string("op_182_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3739520)))]; | |
| tensor<fp16, [1, ?, 384]> linear_7_cast_fp16 = linear(bias = var_182_to_fp16, weight = var_181_to_fp16, x = audio_data)[name = string("linear_7_cast_fp16")]; | |
| tensor<int32, [3]> var_184_shape_cast_fp16 = shape(x = linear_6_cast_fp16)[name = string("op_184_shape_cast_fp16")]; | |
| int32 gather_6_axis_0 = const()[name = string("gather_6_axis_0"), val = int32(0)]; | |
| int32 gather_6_batch_dims_0 = const()[name = string("gather_6_batch_dims_0"), val = int32(0)]; | |
| bool gather_6_validate_indices_0 = const()[name = string("gather_6_validate_indices_0"), val = bool(false)]; | |
| string var_184_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_184_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")]; | |
| uint16 select_6_to_uint16 = const()[name = string("select_6_to_uint16"), val = uint16(1)]; | |
| tensor<uint16, [3]> var_184_shape_cast_fp16_to_uint16 = cast(dtype = var_184_shape_cast_fp16_to_uint16_dtype_0, x = var_184_shape_cast_fp16)[name = string("cast_19")]; | |
| uint16 gather_6_cast_uint16 = gather(axis = gather_6_axis_0, batch_dims = gather_6_batch_dims_0, indices = select_6_to_uint16, validate_indices = gather_6_validate_indices_0, x = var_184_shape_cast_fp16_to_uint16)[name = string("gather_6_cast_uint16")]; | |
| string gather_6_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_6_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_35_axes_0 = const()[name = string("expand_dims_35_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_6_cast_uint16_to_int32 = cast(dtype = gather_6_cast_uint16_to_int32_dtype_0, x = gather_6_cast_uint16)[name = string("cast_18")]; | |
| tensor<int32, [1]> expand_dims_35 = expand_dims(axes = expand_dims_35_axes_0, x = gather_6_cast_uint16_to_int32)[name = string("expand_dims_35")]; | |
| tensor<int32, [4]> concat_23 = const()[name = string("concat_23"), val = tensor<int32, [4]>([3, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_24_values0_0 = const()[name = string("concat_24_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_24_values1_0 = const()[name = string("concat_24_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_24_values3_0 = const()[name = string("concat_24_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_24_axis_0 = const()[name = string("concat_24_axis_0"), val = int32(0)]; | |
| bool concat_24_interleave_0 = const()[name = string("concat_24_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (concat_24_values0_0, concat_24_values1_0, expand_dims_35, concat_24_values3_0))[name = string("concat_24")]; | |
| tensor<int32, [4]> k_cache2_internal_tensor_assign_4_stride_0 = const()[name = string("k_cache2_internal_tensor_assign_4_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_4_begin_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_4_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_4_end_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_4_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> k_cache2_internal_tensor_assign_4_squeeze_mask_0 = const()[name = string("k_cache2_internal_tensor_assign_4_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> k_cache2_internal_tensor_assign_4_cast_fp16 = slice_update(begin = concat_23, begin_mask = k_cache2_internal_tensor_assign_4_begin_mask_0, end = concat_24, end_mask = k_cache2_internal_tensor_assign_4_end_mask_0, squeeze_mask = k_cache2_internal_tensor_assign_4_squeeze_mask_0, stride = k_cache2_internal_tensor_assign_4_stride_0, update = linear_6_cast_fp16, x = coreml_update_state_16)[name = string("k_cache2_internal_tensor_assign_4_cast_fp16")]; | |
| write_state(data = k_cache2_internal_tensor_assign_4_cast_fp16, input = k_cache2)[name = string("coreml_update_state_18_write_state")]; | |
| tensor<int32, [3]> var_189_shape_cast_fp16 = shape(x = linear_7_cast_fp16)[name = string("op_189_shape_cast_fp16")]; | |
| int32 gather_7_axis_0 = const()[name = string("gather_7_axis_0"), val = int32(0)]; | |
| int32 gather_7_batch_dims_0 = const()[name = string("gather_7_batch_dims_0"), val = int32(0)]; | |
| bool gather_7_validate_indices_0 = const()[name = string("gather_7_validate_indices_0"), val = bool(false)]; | |
| string var_189_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_189_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")]; | |
| uint16 select_7_to_uint16 = const()[name = string("select_7_to_uint16"), val = uint16(1)]; | |
| tensor<uint16, [3]> var_189_shape_cast_fp16_to_uint16 = cast(dtype = var_189_shape_cast_fp16_to_uint16_dtype_0, x = var_189_shape_cast_fp16)[name = string("cast_17")]; | |
| uint16 gather_7_cast_uint16 = gather(axis = gather_7_axis_0, batch_dims = gather_7_batch_dims_0, indices = select_7_to_uint16, validate_indices = gather_7_validate_indices_0, x = var_189_shape_cast_fp16_to_uint16)[name = string("gather_7_cast_uint16")]; | |
| string gather_7_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_7_cast_uint16_to_int32_dtype_0"), val = string("int32")]; | |
| tensor<int32, [1]> expand_dims_39_axes_0 = const()[name = string("expand_dims_39_axes_0"), val = tensor<int32, [1]>([0])]; | |
| int32 gather_7_cast_uint16_to_int32 = cast(dtype = gather_7_cast_uint16_to_int32_dtype_0, x = gather_7_cast_uint16)[name = string("cast_16")]; | |
| tensor<int32, [1]> expand_dims_39 = expand_dims(axes = expand_dims_39_axes_0, x = gather_7_cast_uint16_to_int32)[name = string("expand_dims_39")]; | |
| tensor<int32, [4]> concat_26 = const()[name = string("concat_26"), val = tensor<int32, [4]>([3, 0, 0, 0])]; | |
| tensor<int32, [1]> concat_27_values0_0 = const()[name = string("concat_27_values0_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_27_values1_0 = const()[name = string("concat_27_values1_0"), val = tensor<int32, [1]>([0])]; | |
| tensor<int32, [1]> concat_27_values3_0 = const()[name = string("concat_27_values3_0"), val = tensor<int32, [1]>([0])]; | |
| int32 concat_27_axis_0 = const()[name = string("concat_27_axis_0"), val = int32(0)]; | |
| bool concat_27_interleave_0 = const()[name = string("concat_27_interleave_0"), val = bool(false)]; | |
| tensor<int32, [4]> concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (concat_27_values0_0, concat_27_values1_0, expand_dims_39, concat_27_values3_0))[name = string("concat_27")]; | |
| tensor<int32, [4]> v_cache2_internal_tensor_assign_4_stride_0 = const()[name = string("v_cache2_internal_tensor_assign_4_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_4_begin_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_4_begin_mask_0"), val = tensor<bool, [4]>([false, false, false, false])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_4_end_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_4_end_mask_0"), val = tensor<bool, [4]>([false, true, false, true])]; | |
| tensor<bool, [4]> v_cache2_internal_tensor_assign_4_squeeze_mask_0 = const()[name = string("v_cache2_internal_tensor_assign_4_squeeze_mask_0"), val = tensor<bool, [4]>([true, false, false, false])]; | |
| tensor<fp16, [4, 1, 1500, 384]> v_cache2_internal_tensor_assign_4_cast_fp16 = slice_update(begin = concat_26, begin_mask = v_cache2_internal_tensor_assign_4_begin_mask_0, end = concat_27, end_mask = v_cache2_internal_tensor_assign_4_end_mask_0, squeeze_mask = v_cache2_internal_tensor_assign_4_squeeze_mask_0, stride = v_cache2_internal_tensor_assign_4_stride_0, update = linear_7_cast_fp16, x = coreml_update_state_17)[name = string("v_cache2_internal_tensor_assign_4_cast_fp16")]; | |
| write_state(data = v_cache2_internal_tensor_assign_4_cast_fp16, input = v_cache2)[name = string("coreml_update_state_19_write_state")]; | |
| } -> (dummy); | |
| } |