add missing conv2d got dropped somehow

Author: pkmital

python/libs/connections.py

@@ -109,3 +109,55 @@ def linear(x, n_units, scope=None, stddev=0.02,
         matrix = tf.get_variable("Matrix", [shape[1], n_units], tf.float32,
                                  tf.random_normal_initializer(stddev=stddev))
         return activation(tf.matmul(x, matrix))
+
+
+def conv2d(x, n_filters,
+           k_h=5, k_w=5,
+           stride_h=2, stride_w=2,
+           stddev=0.02,
+           activation=lambda x: x,
+           bias=True,
+           padding='SAME',
+           name="Conv2D"):
+    """2D Convolution with options for kernel size, stride, and init deviation.
+
+    Parameters
+    ----------
+    x : Tensor
+        Input tensor to convolve.
+    n_filters : int
+        Number of filters to apply.
+    k_h : int, optional
+        Kernel height.
+    k_w : int, optional
+        Kernel width.
+    stride_h : int, optional
+        Stride in rows.
+    stride_w : int, optional
+        Stride in cols.
+    stddev : float, optional
+        Initialization's standard deviation.
+    activation : arguments, optional
+        Function which applies a nonlinearity
+    padding : str, optional
+        'SAME' or 'VALID'
+    name : str, optional
+        Variable scope to use.
+
+    Returns
+    -------
+    x : Tensor
+        Convolved input.
+    """
+    with tf.variable_scope(name):
+        w = tf.get_variable(
+            'w', [k_h, k_w, x.get_shape()[-1], n_filters],
+            initializer=tf.truncated_normal_initializer(stddev=stddev))
+        conv = tf.nn.conv2d(
+            x, w, strides=[1, stride_h, stride_w, 1], padding=padding)
+        if bias:
+            b = tf.get_variable(
+                'b', [n_filters],
+                initializer=tf.truncated_normal_initializer(stddev=stddev))
+            conv = conv + b
+        return conv