From ddeac78759f2e250ed4b21310e5c3c48e7f3ca81 Mon Sep 17 00:00:00 2001
From: Hui Zhang <zhtclz@foxmail.com>
Date: Tue, 3 Dec 2019 19:59:05 +0800
Subject: [PATCH] fix asr output name

---
 delta/models/asr_model.py            |  2 +-
 egs/hkust/asr/v1/conf/asr-ctc.yml    | 22 +---------------------
 egs/mini_an4/asr/v1/conf/asr-ctc.yml | 22 +---------------------
 3 files changed, 3 insertions(+), 43 deletions(-)

diff --git a/delta/models/asr_model.py b/delta/models/asr_model.py
index 6214854c..852a9973 100644
--- a/delta/models/asr_model.py
+++ b/delta/models/asr_model.py
@@ -244,7 +244,7 @@ def build(self):
                 x)
 
     # Output layer with softmax
-    x = TimeDistributed(Dense(self._vocab_size))(x)
+    x = TimeDistributed(Dense(self._vocab_size), name="outputs")(x)
 
     input_length = Input(name='input_length', shape=[], dtype='int64')
     labels = Input(name='targets', shape=[None], dtype='int32')
diff --git a/egs/hkust/asr/v1/conf/asr-ctc.yml b/egs/hkust/asr/v1/conf/asr-ctc.yml
index 1d729722..5cd4861e 100644
--- a/egs/hkust/asr/v1/conf/asr-ctc.yml
+++ b/egs/hkust/asr/v1/conf/asr-ctc.yml
@@ -36,7 +36,7 @@ data:
       batch_strategy: auto # strategy to count maximum size of batch(support 4 values: "auto", "seq", "frame", "bin")
     batch_mode: true # ture, user control batch; false, `generate` will yeild one example
     num_parallel_calls: 10
-    num_prefetch_batch: 2
+    num_prefetch_batch: 20
     shuffle_buffer_size: 2000
     need_shuffle: true
     sortagrad: true
@@ -58,10 +58,6 @@ model:
 
 solver:
   name: AsrSolver
-  adversarial:
-    enable: false # whether to using adversiral training
-    adv_alpha: 0.5 # adviseral alpha of loss
-    adv_epslion: 0.1 # adviseral example epslion
   model_average:
     enable: false # use average model
     var_avg_decay: 0.99 # the decay rate of varaibles
@@ -96,17 +92,6 @@ solver:
     cals:
     - name: AccuracyCal
       arguments: null
-    - name: ConfusionMatrixCal
-      arguments: null
-    - name: PrecisionCal
-      arguments:
-        average: 'binary'
-    - name: RecallCal
-      arguments:
-        average: 'binary'
-    - name: F1ScoreCal
-      arguments:
-        average: 'binary'
   postproc:
       enbale: false
       name: EmoPostProc
@@ -114,11 +99,6 @@ solver:
       eval: true # compute metrics
       infer: true  # get predict results
       pred_path: null # None for `model_path`/infer, dumps infer output to this dir
-      thresholds:
-          - 0.5
-      smoothing:
-          enable: true
-          count: 2
   saver:
     model_path: "exp/asr-ctc/ckpt"
     max_to_keep: 10
diff --git a/egs/mini_an4/asr/v1/conf/asr-ctc.yml b/egs/mini_an4/asr/v1/conf/asr-ctc.yml
index 875d12d7..9345aae2 100644
--- a/egs/mini_an4/asr/v1/conf/asr-ctc.yml
+++ b/egs/mini_an4/asr/v1/conf/asr-ctc.yml
@@ -36,7 +36,7 @@ data:
       batch_strategy: auto # strategy to count maximum size of batch(support 4 values: "auto", "seq", "frame", "bin")
     batch_mode: true # ture, user control batch; false, `generate` will yeild one example
     num_parallel_calls: 10
-    num_prefetch_batch: 2
+    num_prefetch_batch: 20
     shuffle_buffer_size: 2000
     need_shuffle: true
     sortagrad: true
@@ -58,10 +58,6 @@ model:
 
 solver:
   name: AsrSolver
-  adversarial:
-    enable: false # whether to using adversiral training
-    adv_alpha: 0.5 # adviseral alpha of loss
-    adv_epslion: 0.1 # adviseral example epslion
   model_average:
     enable: false # use average model
     var_avg_decay: 0.99 # the decay rate of varaibles
@@ -96,17 +92,6 @@ solver:
     cals:
     - name: AccuracyCal
       arguments: null
-    - name: ConfusionMatrixCal
-      arguments: null
-    - name: PrecisionCal
-      arguments:
-        average: 'binary'
-    - name: RecallCal
-      arguments:
-        average: 'binary'
-    - name: F1ScoreCal
-      arguments:
-        average: 'binary'
   postproc:
       enbale: false
       name: EmoPostProc
@@ -114,11 +99,6 @@ solver:
       eval: true # compute metrics
       infer: true  # get predict results
       pred_path: null # None for `model_path`/infer, dumps infer output to this dir
-      thresholds:
-          - 0.5
-      smoothing:
-          enable: true
-          count: 2
   saver:
     model_path: "exp/asr-ctc/ckpt"
     max_to_keep: 10