f516cc6ddefeeecec0e42e1f25deee24737af2bc,keras/applications/resnet50.py,,ResNet50,#Any#Any#Any#Any#Any#Any#,127

Before Change

    // load weights
    if weights == "imagenet":
        if K.image_data_format() == "channels_first":
            if include_top:
                weights_path = get_file("resnet50_weights_th_dim_ordering_th_kernels.h5",
                                        TH_WEIGHTS_PATH,
                                        cache_subdir="models",
                                        md5_hash="1c1f8f5b0c8ee28fe9d950625a230e1c")
            else:
                weights_path = get_file("resnet50_weights_th_dim_ordering_th_kernels_notop.h5",
                                        TH_WEIGHTS_PATH_NO_TOP,
                                        cache_subdir="models",
                                        md5_hash="f64f049c92468c9affcd44b0976cdafe")
            model.load_weights(weights_path)
            if K.backend() == "tensorflow":
                warnings.warn("You are using the TensorFlow backend, yet you "
                              "are using the Theano "
                              "image data format convention "
                              "(`image_data_format="channels_first"`). "
                              "For best performance, set "
                              "`image_data_format="channels_last"` in "
                              "your Keras config "
                              "at ~/.keras/keras.json.")
                convert_all_kernels_in_model(model)
        else:
            if include_top:
                weights_path = get_file("resnet50_weights_tf_dim_ordering_tf_kernels.h5",
                                        TF_WEIGHTS_PATH,
                                        cache_subdir="models",
                                        md5_hash="a7b3fe01876f51b976af0dea6bc144eb")
            else:
                weights_path = get_file("resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5",
                                        TF_WEIGHTS_PATH_NO_TOP,
                                        cache_subdir="models",
                                        md5_hash="a268eb855778b3df3c7506639542a6af")
            model.load_weights(weights_path)
            if K.backend() == "theano":
                convert_all_kernels_in_model(model)
    return model

After Change

        if K.backend() == "theano":
            layer_utils.convert_all_kernels_in_model(model)

        if K.image_data_format() == "channels_first":
            if include_top:
                maxpool = model.get_layer(name="avg_pool")
                shape = maxpool.output_shape[1:]
                dense = model.get_layer(name="fc1000")
                layer_utils.convert_dense_weights_data_format(dense, shape, "channels_first")

            if K.backend() == "tensorflow":
                warnings.warn("You are using the TensorFlow backend, yet you "
                              "are using the Theano "
                              "image data format convention "
                              "(`image_data_format="channels_first"`). "
                              "For best performance, set "
                              "`image_data_format="channels_last"` in "
                              "your Keras config "
                              "at ~/.keras/keras.json.")
    return model

Instances