Commit 10a69fbd authored by Laanait, Nouamane's avatar Laanait, Nouamane
Browse files

moving hard coded final layer in YNet() to network_utils.py

parent b0dbdb48

stemdl/network.py

+12 −12
Original line number Diff line number Diff line
@@ -2787,18 +2787,18 @@ class YNet(FCDenseNet, FCNet): 
                #     self._activation_summary(out)

                #     self._activation_image_summary(out)

        

        with tf.variable_scope('%s_CONV_FIN' % subnet, reuse=self.reuse) as scope:

            conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [3, 3], 'padding': 'SAME', 'features': 1})

            self.print_verbose(">>> Adding CONV_FIN layer: ")

            self.print_verbose('    input: %s' %format(out.get_shape().as_list()))

            out, _ = self._conv(input=out, params=conv_1by1) 

            self.print_verbose('    output: %s' %format(out.get_shape().as_list()))

            out_shape = out.get_shape().as_list()

            self._print_layer_specs(layer_params, scope, in_shape, out_shape)

            self.scopes.append(scope) 

            if self.summary: 

                self._activation_summary(out)

                self._activation_image_summary(out) 

        # with tf.variable_scope('%s_CONV_FIN' % subnet, reuse=self.reuse) as scope:

        #     conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [3, 3], 'padding': 'SAME', 'features': 1})

        #     self.print_verbose(">>> Adding CONV_FIN layer: ")

        #     self.print_verbose('    input: %s' %format(out.get_shape().as_list()))

        #     out, _ = self._conv(input=out, params=conv_1by1) 

        #     self.print_verbose('    output: %s' %format(out.get_shape().as_list()))

        #     out_shape = out.get_shape().as_list()

        #     self._print_layer_specs(layer_params, scope, in_shape, out_shape)

        #     self.scopes.append(scope) 

        #     if self.summary: 

        #         self._activation_summary(out)

        #         self._activation_image_summary(out) 

        self.model_output[subnet] = out

        self.update_all_attrs(subnet=subnet)

        self.print_rank('Total # of blocks: %d,  weights: %2.1e, memory: %s MB, ops: %3.2e \n' % (len(network),

stemdl/network_utils.py

+12 −12
Original line number Diff line number Diff line
@@ -437,10 +437,10 @@ def generate_YNet_json(save= True, out_dir='json_files', n_pool=3, n_layers_per_ 
            rank += 1

        features = features // 2

    # 1x1 conv

    # conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [1, 1], 'features': output_channels,

    #                         'activation': None, 'padding': 'SAME', 'batch_norm': False}) 

    # layers_params_list.append(conv_1by1)

    # layers_keys_list.append('CONV_FIN')

    conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [3, 3], 'features': output_channels,

                            'activation': activation, 'padding': 'SAME', 'batch_norm': False}) 

    layers_params_list.append(conv_1by1)

    layers_keys_list.append('CONV_FIN')

    model_keys.append('decoder_RE')

    model_params.append(OrderedDict(zip(layers_keys_list, layers_params_list)))
@@ -463,10 +463,10 @@ def generate_YNet_json(save= True, out_dir='json_files', n_pool=3, n_layers_per_ 
            rank += 1

        features = features // 2

    # 1x1 conv

    # conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [1, 1], 'features': output_channels,

    #                         'activation': None, 'padding': 'SAME', 'batch_norm': False}) 

    # layers_params_list.append(conv_1by1)

    # layers_keys_list.append('CONV_FIN')

    conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [3, 3], 'features': output_channels,

                            'activation': activation, 'padding': 'SAME', 'batch_norm': False}) 

    layers_params_list.append(conv_1by1)

    layers_keys_list.append('CONV_FIN')

    model_keys.append('decoder_IM')

    model_params.append(OrderedDict(zip(layers_keys_list, layers_params_list)))
@@ -498,10 +498,10 @@ def generate_YNet_json(save= True, out_dir='json_files', n_pool=3, n_layers_per_ 
        features = features // 2



    # 1x1 conv

    # conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [1, 1], 'features': output_channels,

    #                         'activation': None, 'padding': 'SAME', 'batch_norm': False}) 

    # layers_params_list.append(conv_1by1)

    # layers_keys_list.append('CONV_FIN')

    conv_1by1 = OrderedDict({'type': 'conv_2D', 'stride': [1, 1], 'kernel': [3, 3], 'features': output_channels,

                            'activation': activation, 'padding': 'SAME', 'batch_norm': False}) 

    layers_params_list.append(conv_1by1)

    layers_keys_list.append('CONV_FIN')

    model_keys.append('inverter')

    model_params.append(OrderedDict(zip(layers_keys_list, layers_params_list)))