{"action":"created","comment":{"url":"https://api.github.com/repos/NVIDIA/OpenSeq2Seq/pulls/comments/205598634","pull_request_review_id":140904248,"id":205598634,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIwNTU5ODYzNA==","diff_hunk":"@@ -11,152 +11,165 @@\n base_model = Speech2Text\n \n base_params = {\n-  \"random_seed\": 0,\n-  \"use_horovod\": False,\n-  \"num_epochs\": 50,\n-\n-  \"num_gpus\": 8,\n-  \"batch_size_per_gpu\": 32,\n-\n-  \"save_summaries_steps\": 100,\n-  \"print_loss_steps\": 10,\n-  \"print_samples_steps\": 2200,\n-  \"eval_steps\": 2200,\n-  \"save_checkpoint_steps\": 1000,\n-  \"logdir\": \"w2l_log_folder\",\n-\n-  \"optimizer\": \"Momentum\",\n-  \"optimizer_params\": {\n-    \"momentum\": 0.90,\n-  },\n-  \"lr_policy\": poly_decay,\n-  \"lr_policy_params\": {\n-    \"learning_rate\": 0.001,\n-    \"power\": 0.5,\n-  },\n-  \"larc_params\": {\n-    \"larc_eta\": 0.001,\n-  },\n-\n-  \"regularizer\": tf.contrib.layers.l2_regularizer,\n-  \"regularizer_params\": {\n-    'scale': 0.0005\n-  },\n-\n-  #\"max_grad_norm\": 15.0,\n-  \"dtype\": tf.float32,\n-\n-  \"summaries\": ['learning_rate', 'variables', 'gradients', 'larc_summaries',\n-                'variable_norm', 'gradient_norm', 'global_gradient_norm'],\n-\n-  \"encoder\": Wave2LetterEncoder,\n-  \"encoder_params\": {\n-    \"convnet_layers\": [\n-      {\n-        \"type\": \"conv1d\", \"repeat\" : 5,\n-        \"kernel_size\": [7], \"stride\": [1],\n-        \"num_channels\": 200, \"padding\": \"SAME\"\n-      },\n-      {\n-        \"type\": \"conv1d\", \"repeat\" : 3,\n-        \"kernel_size\": [11], \"stride\": [1],\n-        \"num_channels\": 400, \"padding\": \"SAME\"\n-      },\n-      {\n-        \"type\": \"conv1d\", \"repeat\" : 3,\n-        \"kernel_size\": [15], \"stride\": [1],\n-        \"num_channels\": 400, \"padding\": \"SAME\"\n-      },\n-      {\n-        \"type\": \"conv1d\", \"repeat\" : 3,\n-        \"kernel_size\": [19], \"stride\": [1],\n-        \"num_channels\": 400, \"padding\": \"SAME\"\n-      },\n-      {\n-        \"type\": \"conv1d\", \"repeat\" : 3,\n-        \"kernel_size\": [23], \"stride\": [1],\n-        \"num_channels\": 600, \"padding\": \"SAME\"\n-      },\n-      {\n-        \"type\": \"conv1d\", \"repeat\" : 1,\n-        \"kernel_size\": [29], \"stride\": [1],\n-        \"num_channels\": 800, \"padding\": \"SAME\"\n-      },\n-      {\n-        \"type\": \"conv1d\", \"repeat\" : 1,\n-        \"kernel_size\": [1], \"stride\": [1],\n-        \"num_channels\": 1000, \"padding\": \"SAME\"\n-      },\n-    ],\n-\n-    \"dropout_keep_prob\": 0.8,\n-\n-    \"initializer\": tf.contrib.layers.xavier_initializer,\n-    \"initializer_params\": {\n-      'uniform': False,\n+    \"random_seed\": 0,\n+    \"use_horovod\": True,\n+    \"num_epochs\": 50,\n+\n+    \"num_gpus\": 8,\n+    \"batch_size_per_gpu\": 64,\n+    \"iter_size\": 1,\n+\n+    \"save_summaries_steps\": 100,\n+    \"print_loss_steps\": 10,\n+    \"print_samples_steps\": 2200,\n+    \"eval_steps\": 2200,\n+    \"save_checkpoint_steps\": 1100,\n+    \"logdir\": \"w2l_log_folder\",\n+\n+    \"optimizer\": \"Momentum\",\n+    \"optimizer_params\": {\n+        \"momentum\": 0.90,\n     },\n-    \"normalization\" : \"batch_norm\",\n-    \"activation_fn\" : lambda x: tf.minimum(tf.nn.relu(x), 20.0),\n-    \"data_format\": \"channels_last\",\n-  },\n-\n-  \"decoder\": FullyConnectedCTCDecoder,\n-  \"decoder_params\": {\n-    \"initializer\": tf.contrib.layers.xavier_initializer,\n-    \"use_language_model\": True,\n-\n-    # params for decoding the sequence with language model\n-    \"beam_width\": 512,\n-    \"lm_weight\": 2.0,\n-    \"word_count_weight\": 1.5,\n-    \"valid_word_count_weight\": 2.5,\n-\n-    \"decoder_library_path\": \"ctc_decoder_with_lm/libctc_decoder_with_kenlm.so\",\n-    \"lm_binary_path\": \"language_model/lm.binary\",\n-    \"lm_trie_path\": \"language_model/trie\",\n-    \"alphabet_config_path\": \"open_seq2seq/test_utils/toy_speech_data/vocab.txt\",\n-  },\n-  \"loss\": CTCLoss,\n-  \"loss_params\": {},\n+    \"lr_policy\": poly_decay,\n+    #\"lr_policy\": fixed_lr,\n+    \"lr_policy_params\": {\n+        \"learning_rate\": 0.1,\n+        \"power\": 2.0,\n+    },\n+    \"larc_params\": {\n+        \"larc_eta\": 0.001,\n+    },\n+    \"larc_params\": {\n+        \"larc_eta\": 0.001,\n+    },\n+\n+    \"regularizer\": tf.contrib.layers.l2_regularizer,\n+    \"regularizer_params\": {\n+        'scale': 0.001\n+    },\n+\n+    #\"max_grad_norm\": 15.0,\n+    \"dtype\": tf.float32,\n+\n+    \"summaries\": ['learning_rate', 'variables', 'gradients', 'larc_summaries',\n+                  'variable_norm', 'gradient_norm', 'global_gradient_norm'],\n+\n+    \"encoder\": Wave2LetterEncoder,\n+    \"encoder_params\": {\n+        \"convnet_layers\": [\n+            {\n+                \"type\": \"conv1d\", \"repeat\": 3,\n+                \"kernel_size\": [11], \"stride\": [1],\n+                \"num_channels\": 256, \"padding\": \"SAME\",\n+                \"dropout_keep_prob\": 0.8,\n+            },\n+            {\n+                \"type\": \"conv1d\", \"repeat\": 3,\n+                \"kernel_size\": [13], \"stride\": [1],\n+                \"num_channels\": 384, \"padding\": \"SAME\",\n+                \"dropout_keep_prob\": 0.8,\n+            },\n+            {\n+                \"type\": \"conv1d\", \"repeat\": 3,\n+                \"kernel_size\": [17], \"stride\": [1],\n+                \"num_channels\": 512, \"padding\": \"SAME\",\n+                \"dropout_keep_prob\": 0.8,\n+            },\n+            {\n+                \"type\": \"conv1d\", \"repeat\": 3,\n+                \"kernel_size\": [21], \"stride\": [1],\n+                \"num_channels\": 640, \"padding\": \"SAME\",\n+                \"dropout_keep_prob\": 0.7,\n+            },\n+            {\n+                \"type\": \"conv1d\", \"repeat\": 3,\n+                \"kernel_size\": [25], \"stride\": [1],\n+                \"num_channels\": 768, \"padding\": \"SAME\",\n+                \"dropout_keep_prob\": 0.7,\n+            },\n+            {\n+                \"type\": \"conv1d\", \"repeat\": 1,\n+                \"kernel_size\": [29], \"stride\": [1],\n+                \"num_channels\": 896, \"padding\": \"SAME\",\n+                \"dropout_keep_prob\": 0.6,\n+            },\n+            {\n+                \"type\": \"conv1d\", \"repeat\": 1,\n+                \"kernel_size\": [1], \"stride\": [1],\n+                \"num_channels\": 1024, \"padding\": \"SAME\",\n+                \"dropout_keep_prob\": 0.6,\n+            },\n+        ],\n+\n+        \"dropout_keep_prob\": 0.8,\n+\n+        \"initializer\": tf.contrib.layers.xavier_initializer,\n+        \"initializer_params\": {\n+            'uniform': False,\n+        },\n+        \"normalization\": \"batch_norm\",\n+        \"activation_fn\": lambda x: tf.minimum(tf.nn.relu(x), 20.0),\n+        \"data_format\": \"channels_last\",\n+    },\n+\n+    \"decoder\": FullyConnectedCTCDecoder,\n+    \"decoder_params\": {\n+        \"initializer\": tf.contrib.layers.xavier_initializer,\n+        \"use_language_model\": False,\n+\n+        # params for decoding the sequence with language model\n+        \"beam_width\": 512,\n+        \"lm_weight\": 2.0,\n+        \"word_count_weight\": 1.5,\n+        \"valid_word_count_weight\": 2.5,\n+\n+        \"decoder_library_path\": \"ctc_decoder_with_lm/libctc_decoder_with_kenlm.so\",\n+        \"lm_binary_path\": \"language_model/lm.binary\",\n+        \"lm_trie_path\": \"language_model/trie\",\n+        \"alphabet_config_path\": \"open_seq2seq/test_utils/toy_speech_data/vocab.txt\",\n+    },\n+    \"loss\": CTCLoss,\n+    \"loss_params\": {},\n }\n \n train_params = {\n-  \"data_layer\": Speech2TextDataLayer,\n-  \"data_layer_params\": {\n-    \"num_audio_features\": 40,\n-    \"input_type\": \"logfbank\",\n-    \"vocab_file\": 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\"/data/librispeech/librivox-train-clean-100.csv\",","path":"example_configs/speech2text/w2l_large_8gpus.py","position":250,"original_position":250,"commit_id":"3591c9d13fc62629277c79a2ad856ada2dc9b21d","original_commit_id":"3591c9d13fc62629277c79a2ad856ada2dc9b21d","user":{"login":"vsl9","id":4344862,"node_id":"MDQ6VXNlcjQzNDQ4NjI=","avatar_url":"https://avatars2.githubusercontent.com/u/4344862?v=4","gravatar_id":"","url":"https://api.github.com/users/vsl9","html_url":"https://github.com/vsl9","followers_url":"https://api.github.com/users/vsl9/followers","following_url":"https://api.github.com/users/vsl9/following{/other_user}","gists_url":"https://api.github.com/users/vsl9/gists{/gist_id}","starred_url":"https://api.github.com/users/vsl9/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vsl9/subscriptions","organizations_url":"https://api.github.com/users/vsl9/orgs","repos_url":"https://api.github.com/users/vsl9/repos","events_url":"https://api.github.com/users/vsl9/events{/privacy}","received_events_url":"https://api.github.com/users/vsl9/received_events","type":"User","site_admin":false},"body":"Please set path prefix to \"data\" (instead of \"/data\")  to be consistent with other configs (DS2).","created_at":"2018-07-26T20:52:13Z","updated_at":"2018-07-26T20:52:13Z","html_url":"https://github.com/NVIDIA/OpenSeq2Seq/pull/194#discussion_r205598634","pull_request_url":"https://api.github.com/repos/NVIDIA/OpenSeq2Seq/pulls/194","author_association":"COLLABORATOR","_links":{"self":{"href":"https://api.github.com/repos/NVIDIA/OpenSeq2Seq/pulls/comments/205598634"},"html":{"href":"https://github.com/NVIDIA/OpenSeq2Seq/pull/194#discussion_r205598634"},"pull_request":{"href":"https://api.github.com/repos/NVIDIA/OpenSeq2Seq/pulls/194"}}},"pull_request":{"url":"https://api.github.com/repos/NVIDIA/OpenSeq2Seq/pulls/194","id":203998135,"node_id":"MDExOlB1bGxSZXF1ZXN0MjAzOTk4MTM1","html_url":"https://github.com/NVIDIA/OpenSeq2Seq/pull/194","diff_url":"https://github.com/NVIDIA/OpenSeq2Seq/pull/194.diff","patch_url":"https://github.com/NVIDIA/OpenSeq2Seq/pull/194.patch","issue_url":"https://api.github.com/repos/NVIDIA/OpenSeq2Seq/issues/194","number":194,"state":"open","locked":false,"title":"Wave2Letter 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