Rm flaky summary histogram

PiperOrigin-RevId: 175362634

Author: Ryan Sepassi

.travis.yml

@@ -24,6 +24,6 @@ script:
   - mkdir $T2T_TRAIN_DIR
   - t2t-datagen --problem=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR
   - t2t-trainer --problems=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR --model=transformer --hparams_set=transformer_tiny --train_steps=5 --eval_steps=5 --output_dir=$T2T_TRAIN_DIR
-  - t2t-decoder --problems=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR --model=transformer --hparams_set=transformer_tiny --output_dir=$T2T_TRAIN_DIR --decode_hparams='num_samples=10,use_last_position_only=True'
+  - t2t-decoder --problems=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR --model=transformer --hparams_set=transformer_tiny --output_dir=$T2T_TRAIN_DIR --decode_hparams='num_samples=10'
 git:
   depth: 3

tensor2tensor/layers/common_layers.py

@@ -1241,10 +1241,6 @@ def conv_hidden_relu(inputs,
         **kwargs)
     if dropout != 0.0:
       h = tf.nn.dropout(h, 1.0 - dropout)
-    if not tf.get_variable_scope().reuse:
-      tf.summary.histogram("hidden_density_logit",
-                           relu_density_logit(
-                               h, list(range(inputs.shape.ndims - 1))))
     conv_f2 = conv if second_kernel_size == (1, 1) else separable_conv
     ret = conv_f2(h, output_size, second_kernel_size, name="conv2", **kwargs)
     if is_3d: