6b106ab4ec9a1c0eb3e24ae590ce63f84022ad40,keras/backend/tensorflow_backend.py,,separable_conv2d,#Any#Any#Any#Any#Any#Any#Any#,3318

Before Change

    x = _preprocess_conv2d_input(x, data_format)
    padding = _preprocess_padding(padding)
    strides = (1,) + strides + (1,)

    x = tf.nn.separable_conv2d(x, depthwise_kernel, pointwise_kernel,
                               strides=strides,
                               padding=padding,
                               rate=dilation_rate)
    return _postprocess_conv2d_output(x, data_format)


def depthwise_conv2d(x, depthwise_kernel, strides=(1, 1), padding="valid",
                     data_format=None, dilation_rate=(1, 1)):

After Change

    if data_format not in {"channels_first", "channels_last"}:
        raise ValueError("Unknown data_format " + str(data_format))

    x, tf_data_format = _preprocess_conv2d_input(x, data_format)
    padding = _preprocess_padding(padding)
    if tf_data_format == "NHWC":
        strides = (1,) + strides + (1,)
    else:
        strides = (1, 1) + strides

    x = tf.nn.separable_conv2d(x, depthwise_kernel, pointwise_kernel,
                               strides=strides,
                               padding=padding,
                               rate=dilation_rate,
                               data_format=tf_data_format)
    if data_format == "channels_first" and tf_data_format == "NHWC":
        x = tf.transpose(x, (0, 3, 1, 2))  // NHWC -> NCHW
    return x


def depthwise_conv2d(x, depthwise_kernel, strides=(1, 1), padding="valid",
                     data_format=None, dilation_rate=(1, 1)):

Instances