Use diff to compare config unittest (#363)

Fix #342

python/paddle/trainer_config_helpers/tests/configs/generate_protostr.sh

@@ -4,6 +4,8 @@ set -e
 cd `dirname $0`
 export PYTHONPATH=$PWD/../../../../
 
+protostr=$PWD/protostr
+
 configs=(test_fc layer_activations projections test_print_layer
 test_sequence_pooling test_lstmemory_layer test_grumemory_layer
 last_first_seq test_expand_layer test_ntm_layers test_hsigmoid
@@ -15,5 +17,5 @@ test_maxout test_bi_grumemory math_ops)
 for conf in ${configs[*]}
 do
     echo "Generating " $conf
-    python -m paddle.utils.dump_config $conf.py > $conf.protostr
+    python -m paddle.utils.dump_config $conf.py > $protostr/$conf.protostr.unitest
 done

python/paddle/trainer_config_helpers/tests/configs/protostr/img_layers.protostr

@@ -0,0 +1,176 @@
+type: "nn"
+layers {
+  name: "image"
+  type: "data"
+  size: 65536
+  active_type: ""
+}
+layers {
+  name: "__conv_0__"
+  type: "exconv"
+  size: 3297856
+  active_type: ""
+  inputs {
+    input_layer_name: "image"
+    input_parameter_name: "___conv_0__.w0"
+    conv_conf {
+      filter_size: 32
+      channels: 1
+      stride: 1
+      padding: 1
+      groups: 1
+      filter_channels: 1
+      output_x: 227
+      img_size: 256
+      caffe_mode: true
+      filter_size_y: 32
+      padding_y: 1
+      stride_y: 1
+    }
+  }
+  bias_parameter_name: "___conv_0__.wbias"
+  num_filters: 64
+  shared_biases: true
+}
+layers {
+  name: "__batch_norm_0__"
+  type: "batch_norm"
+  size: 3297856
+  active_type: "relu"
+  inputs {
+    input_layer_name: "__conv_0__"
+    input_parameter_name: "___batch_norm_0__.w0"
+    image_conf {
+      channels: 64
+      img_size: 227
+    }
+  }
+  inputs {
+    input_layer_name: "__conv_0__"
+    input_parameter_name: "___batch_norm_0__.w1"
+  }
+  inputs {
+    input_layer_name: "__conv_0__"
+    input_parameter_name: "___batch_norm_0__.w2"
+  }
+  bias_parameter_name: "___batch_norm_0__.wbias"
+  moving_average_fraction: 0.9
+}
+layers {
+  name: "__crmnorm_0__"
+  type: "norm"
+  size: 3297856
+  active_type: ""
+  inputs {
+    input_layer_name: "__batch_norm_0__"
+    norm_conf {
+      norm_type: "cmrnorm-projection"
+      channels: 64
+      size: 32
+      scale: 0.0004
+      pow: 0.75
+      output_x: 227
+      img_size: 227
+      blocked: false
+    }
+  }
+}
+layers {
+  name: "__pool_0__"
+  type: "pool"
+  size: 2458624
+  active_type: ""
+  inputs {
+    input_layer_name: "__conv_0__"
+    pool_conf {
+      pool_type: "max-projection"
+      channels: 64
+      size_x: 32
+      stride: 1
+      output_x: 196
+      img_size: 227
+      padding: 0
+      size_y: 32
+      stride_y: 1
+      output_y: 196
+      img_size_y: 227
+      padding_y: 0
+    }
+  }
+}
+parameters {
+  name: "___conv_0__.w0"
+  size: 65536
+  initial_mean: 0.0
+  initial_std: 0.0441941738242
+  initial_strategy: 0
+  initial_smart: false
+}
+parameters {
+  name: "___conv_0__.wbias"
+  size: 64
+  initial_mean: 0.0
+  initial_std: 0.0
+  dims: 64
+  dims: 1
+  initial_strategy: 0
+  initial_smart: false
+}
+parameters {
+  name: "___batch_norm_0__.w0"
+  size: 64
+  initial_mean: 1.0
+  initial_std: 0.0
+  initial_strategy: 0
+  initial_smart: false
+}
+parameters {
+  name: "___batch_norm_0__.w1"
+  size: 64
+  initial_mean: 0.0
+  initial_std: 0.0
+  dims: 1
+  dims: 64
+  initial_strategy: 0
+  initial_smart: false
+  is_static: true
+  is_shared: true
+}
+parameters {
+  name: "___batch_norm_0__.w2"
+  size: 64
+  initial_mean: 0.0
+  initial_std: 0.0
+  dims: 1
+  dims: 64
+  initial_strategy: 0
+  initial_smart: false
+  is_static: true
+  is_shared: true
+}
+parameters {
+  name: "___batch_norm_0__.wbias"
+  size: 64
+  initial_mean: 0.0
+  initial_std: 0.0
+  dims: 1
+  dims: 64
+  initial_strategy: 0
+  initial_smart: false
+}
+input_layer_names: "image"
+output_layer_names: "__pool_0__"
+output_layer_names: "__crmnorm_0__"
+sub_models {
+  name: "root"
+  layer_names: "image"
+  layer_names: "__conv_0__"
+  layer_names: "__batch_norm_0__"
+  layer_names: "__crmnorm_0__"
+  layer_names: "__pool_0__"
+  input_layer_names: "image"
+  output_layer_names: "__pool_0__"
+  output_layer_names: "__crmnorm_0__"
+  is_recurrent_layer_group: false
+}
+

python/paddle/trainer_config_helpers/tests/configs/protostr/last_first_seq.protostr

@@ -0,0 +1,69 @@
+type: "nn"
+layers {
+  name: "data"
+  type: "data"
+  size: 30
+  active_type: ""
+}
+layers {
+  name: "__first_seq_0__"
+  type: "seqlastins"
+  size: 30
+  active_type: "linear"
+  inputs {
+    input_layer_name: "data"
+  }
+  select_first: true
+  trans_type: "seq"
+}
+layers {
+  name: "__first_seq_1__"
+  type: "seqlastins"
+  size: 30
+  active_type: "linear"
+  inputs {
+    input_layer_name: "data"
+  }
+  select_first: true
+  trans_type: "non-seq"
+}
+layers {
+  name: "__last_seq_0__"
+  type: "seqlastins"
+  size: 30
+  active_type: "linear"
+  inputs {
+    input_layer_name: "data"
+  }
+  trans_type: "seq"
+}
+layers {
+  name: "__last_seq_1__"
+  type: "seqlastins"
+  size: 30
+  active_type: "linear"
+  inputs {
+    input_layer_name: "data"
+  }
+  trans_type: "non-seq"
+}
+input_layer_names: "data"
+output_layer_names: "__first_seq_0__"
+output_layer_names: "__first_seq_1__"
+output_layer_names: "__last_seq_0__"
+output_layer_names: "__last_seq_1__"
+sub_models {
+  name: "root"
+  layer_names: "data"
+  layer_names: "__first_seq_0__"
+  layer_names: "__first_seq_1__"
+  layer_names: "__last_seq_0__"
+  layer_names: "__last_seq_1__"
+  input_layer_names: "data"
+  output_layer_names: "__first_seq_0__"
+  output_layer_names: "__first_seq_1__"
+  output_layer_names: "__last_seq_0__"
+  output_layer_names: "__last_seq_1__"
+  is_recurrent_layer_group: false
+}
+