Ternary conv fix (#659)

* ternary conv fix

* _compute_threshold deprecation warning fixed

* Ternary Conv Layer added in unittest + Conv Tests Refactored

* Changelog Updated

* Codacy Error Fix

* TL Logging Prefix for Warning/Error/Fatal added

Author: Jonathan DEKHTIAR

CHANGELOG.md

@@ -107,7 +107,9 @@ To release a new version, please update the changelog as followed:
 - `tl.files` refactored into a directory with numerous files (by @DEKHTIARJonathan in #657)
 - `tl.files.voc_dataset` fixed because of original Pascal VOC website was down (by @DEKHTIARJonathan in #657)
 - extra requirements hidden inside the library added in the project requirements (by @DEKHTIARJonathan in #657)
-- requirements files refactored in `requirements/` directory (by @DEKHTIARJonathan in #657) 
+- requirements files refactored in `requirements/` directory (by @DEKHTIARJonathan in #657)
+- Ternary Convolution Layer added in unittest (by @DEKHTIARJonathan in #658)
+- Convolution Layers unittests have been cleaned & refactored (by @DEKHTIARJonathan in #658)
 
 ### Deprecated
 
@@ -119,6 +121,8 @@ To release a new version, please update the changelog as followed:
 - Issue #565 related to `tl.utils.predict` fixed - `np.hstack` problem in which the results for multiple batches are stacked along `axis=1` (by @2wins in #566)
 - Issue #572 with `tl.layers.DeformableConv2d` fixed (by @DEKHTIARJonathan in #573)
 - Typo of the document of ElementwiseLambdaLayer (by @zsdonghao in #588)
+- Error in `tl.layers.TernaryConv2d` fixed - self.inputs not defined (by @DEKHTIARJonathan in #658)
+- Deprecation warning fixed in `tl.layers.binary._compute_threshold()` (by @DEKHTIARJonathan in #658)
 
 ### Security
 

tensorlayer/files/utils.py

@@ -2087,7 +2087,9 @@ def _dlProgress(count, blockSize, totalSize, pbar=progress_bar):
                 pbar.update(count, force=True)
 
         filepath = os.path.join(working_directory, filename)
-        sys.stdout.write('Downloading %s...\n' % filename)
+
+        logging.info('Downloading %s...\n' % filename)
+
         urlretrieve(url_source + filename, filepath, reporthook=_dlProgress)
 
     exists_or_mkdir(working_directory, verbose=False)

tensorlayer/layers/binary.py

@@ -65,7 +65,7 @@ def _compute_threshold(x):
     ref: https://github.com/XJTUWYD/TWN
     Computing the threshold.
     """
-    x_sum = tf.reduce_sum(tf.abs(x), reduction_indices=None, keep_dims=False, name=None)
+    x_sum = tf.reduce_sum(tf.abs(x), reduction_indices=None, keepdims=False, name=None)
     threshold = tf.div(x_sum, tf.cast(tf.size(x), tf.float32), name=None)
     threshold = tf.multiply(0.7, threshold, name=None)
     return threshold
@@ -408,6 +408,7 @@ def __init__(
                 # self.outputs = act(xnor_gemm(self.inputs, W)) # TODO
 
         self.all_layers.append(self.outputs)
+
         if b_init is not None:
             self.all_params.extend([W, b])
         else:
@@ -500,31 +501,43 @@ def __init__(
             (name, n_filter, str(filter_size), str(strides), padding, act.__name__)
         )
 
+        if len(strides) != 2:
+            raise ValueError("len(strides) should be 2.")
+
+        if use_gemm:
+            raise Exception("TODO. The current version use tf.matmul for inferencing.")
+
         if W_init_args is None:
             W_init_args = {}
+
         if b_init_args is None:
             b_init_args = {}
+
         if act is None:
             act = tf.identity
-        if use_gemm:
-            raise Exception("TODO. The current version use tf.matmul for inferencing.")
 
-        if len(strides) != 2:
-            raise ValueError("len(strides) should be 2.")
         try:
             pre_channel = int(prev_layer.outputs.get_shape()[-1])
         except Exception:  # if pre_channel is ?, it happens when using Spatial Transformer Net
             pre_channel = 1
             logging.info("[warnings] unknow input channels, set to 1")
+
         shape = (filter_size[0], filter_size[1], pre_channel, n_filter)
         strides = (1, strides[0], strides[1], 1)
+
+        self.inputs = prev_layer.outputs
+
         with tf.variable_scope(name):
+
             W = tf.get_variable(
                 name='W_conv2d', shape=shape, initializer=W_init, dtype=LayersConfig.tf_dtype, **W_init_args
             )
+
             alpha = _compute_alpha(W)
+
             W = _ternary_operation(W)
             W = tf.multiply(alpha, W)
+
             if b_init:
                 b = tf.get_variable(
                     name='b_conv2d', shape=(shape[-1]), initializer=b_init, dtype=LayersConfig.tf_dtype, **b_init_args
@@ -535,6 +548,7 @@ def __init__(
                         data_format=data_format
                     ) + b
                 )
+
             else:
                 self.outputs = act(
                     tf.nn.conv2d(
@@ -544,6 +558,7 @@ def __init__(
                 )
 
         self.all_layers.append(self.outputs)
+
         if b_init:
             self.all_params.extend([W, b])
         else:

tensorlayer/tl_logging.py

@@ -86,24 +86,24 @@ def debug(msg, *args, **kwargs):
     _get_logger().debug(msg, *args, **kwargs)
 
 
-def error(msg, *args, **kwargs):
-    _get_logger().error(msg, *args, **kwargs)
+def info(msg, *args, **kwargs):
+    _get_logger().info(msg, *args, **kwargs)
 
 
-def fatal(msg, *args, **kwargs):
-    _get_logger().fatal(msg, *args, **kwargs)
+def error(msg, *args, **kwargs):
+    _get_logger().error("ERROR: %s" % msg, *args, **kwargs)
 
 
-def info(msg, *args, **kwargs):
-    _get_logger().info(msg, *args, **kwargs)
+def fatal(msg, *args, **kwargs):
+    _get_logger().fatal("FATAL: %s" % msg, *args, **kwargs)
 
 
 def warn(msg, *args, **kwargs):
-    _get_logger().warning(msg, *args, **kwargs)
+    warning(msg, *args, **kwargs)
 
 
 def warning(msg, *args, **kwargs):
-    _get_logger().warning(msg, *args, **kwargs)
+    _get_logger().warning("WARNING: %s" % msg, *args, **kwargs)
 
 
 # Mask to convert integer thread ids to unsigned quantities for logging

tensorlayer/visualize.py

@@ -2,24 +2,21 @@
 
 import os
 
-try:
-    import cv2
-except ImportError:
-    import warnings
-    warnings.simplefilter('default', ImportWarning)
-    warnings.warn(
-        message='[TL] Warning: OpenCV Library is not installed.\n' \
-        'The function `tl.visualize.draw_boxes_and_labels_to_image` will not be able to work.',
-        category=ImportWarning
-    )
-
 import imageio
 
 import numpy as np
 
 from tensorlayer import tl_logging as logging
 from tensorlayer import prepro
 
+try:
+    import cv2
+except ImportError:
+    logging.warn(
+        'OpenCV Library is not installed.'
+        'The function `tl.visualize.draw_boxes_and_labels_to_image` will not be able to work.'
+    )
+
 # Uncomment the following line if you got: _tkinter.TclError: no display name and no $DISPLAY environment variable
 # import matplotlib
 # matplotlib.use('Agg')