C++ NetParameter::layers_size方法代码示例

bool UpgradeV1Net(const NetParameter& v1_net_param, NetParameter* net_param) {
  bool is_fully_compatible = true;
  if (v1_net_param.layer_size() > 0) {
    LOG(ERROR) << "Input NetParameter to be upgraded already specifies 'layer' "
               << "fields; these will be ignored for the upgrade.";
    is_fully_compatible = false;
  }
  net_param->CopyFrom(v1_net_param);
  net_param->clear_layers();
  net_param->clear_layer();
  for (int i = 0; i < v1_net_param.layers_size(); ++i) {
    if (!UpgradeV1LayerParameter(v1_net_param.layers(i),
                                 net_param->add_layer())) {
      LOG(ERROR) << "Upgrade of input layer " << i << " failed.";
      is_fully_compatible = false;
    }
  }
  return is_fully_compatible;
}

void NetParameterToPrettyPrint(const NetParameter& param,
                               NetParameterPrettyPrint* pretty_param) {
    pretty_param->Clear();
    if (param.has_name()) {
        pretty_param->set_name(param.name());
    }
    if (param.has_force_backward()) {
        pretty_param->set_force_backward(param.force_backward());
    }
    for (int i = 0; i < param.input_size(); ++i) {
        pretty_param->add_input(param.input(i));
    }
    for (int i = 0; i < param.input_dim_size(); ++i) {
        pretty_param->add_input_dim(param.input_dim(i));
    }
    for (int i = 0; i < param.layers_size(); ++i) {
        pretty_param->add_layers()->CopyFrom(param.layers(i));
    }
}

bool NetNeedsDataUpgrade(const NetParameter& net_param) {
  for (int i = 0; i < net_param.layers_size(); ++i) {
    if (net_param.layers(i).type() == LayerParameter_LayerType_DATA) {
      DataParameter layer_param = net_param.layers(i).data_param();
      if (layer_param.has_scale()) { return true; }
      if (layer_param.has_mean_file()) { return true; }
      if (layer_param.has_crop_size()) { return true; }
      if (layer_param.has_mirror()) { return true; }
    }
    if (net_param.layers(i).type() == LayerParameter_LayerType_IMAGE_DATA) {
      ImageDataParameter layer_param = net_param.layers(i).image_data_param();
      if (layer_param.has_scale()) { return true; }
      if (layer_param.has_mean_file()) { return true; }
      if (layer_param.has_crop_size()) { return true; }
      if (layer_param.has_mirror()) { return true; }
    }
  }
  return false;
}

bool UpgradeV1Net(const NetParameter& v1_net_param, NetParameter* net_param) {
  if (v1_net_param.layer_size() > 0) {
    LOG(FATAL) << "Refusing to upgrade inconsistent NetParameter input; "
        << "the definition includes both 'layer' and 'layers' fields. "
        << "The current format defines 'layer' fields with string type like "
        << "layer { type: 'Layer' ... } and not layers { type: LAYER ... }. "
        << "Manually switch the definition to 'layer' format to continue.";
  }
  bool is_fully_compatible = true;
  net_param->CopyFrom(v1_net_param);
  net_param->clear_layers();
  net_param->clear_layer();
  for (int i = 0; i < v1_net_param.layers_size(); ++i) {
    if (!UpgradeV1LayerParameter(v1_net_param.layers(i),
                                 net_param->add_layer())) {
      LOG(ERROR) << "Upgrade of input layer " << i << " failed.";
      is_fully_compatible = false;
    }
  }
  return is_fully_compatible;
}

bool NetNeedsV1ToV2Upgrade(const NetParameter& net_param) {
  return net_param.layers_size() > 0;
}

void InsertSplits(const NetParameter& param, NetParameter* param_split) {
  // Initialize by copying from the input NetParameter.
  param_split->CopyFrom(param);
  param_split->clear_layers();
  map<string, pair<int, int> > blob_name_to_last_top_idx;
  map<pair<int, int>, pair<int, int> > bottom_idx_to_source_top_idx;
  map<pair<int, int>, int> top_idx_to_bottom_count;
  map<pair<int, int>, int> top_idx_to_bottom_split_idx;
  map<int, string> layer_idx_to_layer_name;
  layer_idx_to_layer_name[-1] = "input";
  // Determine the number of times each blob is used as an input (bottom) blob.
  for (int i = 0; i < param.input_size(); ++i) {
    const string& blob_name = param.input(i);
    blob_name_to_last_top_idx[blob_name] = make_pair(-1, i);
  }
  for (int i = 0; i < param.layers_size(); ++i) {
    const LayerParameter& layer_param = param.layers(i);
    layer_idx_to_layer_name[i] = layer_param.name();
    for (int j = 0; j < layer_param.bottom_size(); ++j) {
      const string& blob_name = layer_param.bottom(j);
      if (blob_name_to_last_top_idx.find(blob_name) ==
          blob_name_to_last_top_idx.end()) {
        LOG(FATAL) << "Unknown blob input " << blob_name << " to layer " << j;
      }
      const pair<int, int>& bottom_idx = make_pair(i, j);
      const pair<int, int>& top_idx = blob_name_to_last_top_idx[blob_name];
      bottom_idx_to_source_top_idx[bottom_idx] = top_idx;
      ++top_idx_to_bottom_count[top_idx];
    }
    for (int j = 0; j < layer_param.top_size(); ++j) {
      const string& blob_name = layer_param.top(j);
      blob_name_to_last_top_idx[blob_name] = make_pair(i, j);
    }
  }
  // Create split layer for any input blobs used by other layers as bottom
  // blobs more than once.
  for (int i = 0; i < param.input_size(); ++i) {
    const int split_count = top_idx_to_bottom_count[make_pair(-1, i)];
    if (split_count > 1) {
      const string& layer_name = layer_idx_to_layer_name[-1];
      const string& blob_name = param.input(i);
      LayerParameter* split_layer_param = param_split->add_layers();
      ConfigureSplitLayer(layer_name, blob_name, i, split_count,
          split_layer_param);
    }
  }
  for (int i = 0; i < param.layers_size(); ++i) {
    LayerParameter* layer_param = param_split->add_layers();
    layer_param->CopyFrom(param.layers(i));
    // Replace any shared bottom blobs with split layer outputs.
    for (int j = 0; j < layer_param->bottom_size(); ++j) {
      const pair<int, int>& top_idx =
          bottom_idx_to_source_top_idx[make_pair(i, j)];
      const int split_count = top_idx_to_bottom_count[top_idx];
      if (split_count > 1) {
        const string& layer_name = layer_idx_to_layer_name[top_idx.first];
        const string& blob_name = layer_param->bottom(j);
        layer_param->set_bottom(j, SplitBlobName(layer_name,
            blob_name, top_idx.second, top_idx_to_bottom_split_idx[top_idx]++));
      }
    }
    // Create split layer for any top blobs used by other layers as bottom
    // blobs more than once.
    for (int j = 0; j < layer_param->top_size(); ++j) {
      const int split_count = top_idx_to_bottom_count[make_pair(i, j)];
      if (split_count > 1) {
        const string& layer_name = layer_idx_to_layer_name[i];
        const string& blob_name = layer_param->top(j);
        LayerParameter* split_layer_param = param_split->add_layers();
        ConfigureSplitLayer(layer_name, blob_name, j, split_count,
            split_layer_param);
      }
    }
  }
}

	void Net<Dtype>::Init(const NetParameter& in_param) {
		// Create a copy of in_param with splits added where necessary.
		NetParameter param;
		InsertSplits(in_param, &param);
		
		// Basically, build all the layers and set up its connections.
		name_ = param.name();
		map<string, int> blob_name_to_idx;
		set<string> available_blobs;
		int num_layers = param.layers_size();
		
		CHECK_EQ(param.input_size() * 4, param.input_dim_size())
			<< "Incorrect bottom blob dimension specifications.";
		size_t memory_used = 0;
		
		// set the input blobs
		for (int i = 0; i < param.input_size(); ++i) {
			const string& blob_name = param.input(i);
			shared_ptr<Blob<Dtype> > blob_pointer(
				new Blob<Dtype>(param.input_dim(i * 4),
				param.input_dim(i * 4 + 1),
				param.input_dim(i * 4 + 2),
				param.input_dim(i * 4 + 3)));
			blobs_.push_back(blob_pointer);
			blob_names_.push_back(blob_name);
			blob_need_backward_.push_back(param.force_backward());
			net_input_blob_indices_.push_back(i);
			net_input_blobs_.push_back(blob_pointer.get());
			blob_name_to_idx[blob_name] = i;
			available_blobs.insert(blob_name);
			memory_used += blob_pointer->count();
		}
		DLOG(INFO) << "Memory required for Data" << memory_used*sizeof(Dtype);
		
		// For each layer, set up their input and output
		bottom_vecs_.resize(param.layers_size());
		top_vecs_.resize(param.layers_size());
		bottom_id_vecs_.resize(param.layers_size());
		top_id_vecs_.resize(param.layers_size());
		
		for (int i = 0; i < param.layers_size(); ++i) {
			bool in_place = false;
			const LayerParameter& layer_param = param.layers(i);
			layers_.push_back(shared_ptr<Layer<Dtype> >(GetLayer<Dtype>(layer_param)));
			layer_names_.push_back(layer_param.name());
			
			LOG(INFO) << "Creating Layer " << layer_param.name();
			bool need_backward = param.force_backward();
			
			// Figure out this layer's input
			for (int j = 0; j < layer_param.bottom_size(); ++j) {
				const string& blob_name = layer_param.bottom(j);
				const int blob_id = blob_name_to_idx[blob_name];
				if (available_blobs.find(blob_name) == available_blobs.end()) {
					LOG(FATAL) << "Unknown blob input " << blob_name <<
						" to layer" << j;
				}
				LOG(INFO) << layer_param.name() << " <- " << blob_name;
				bottom_vecs_[i].push_back(blobs_[blob_id].get());
				bottom_id_vecs_[i].push_back(blob_id);
				// If a blob needs backward, this layer should provide it.
				need_backward |= blob_need_backward_[blob_id];
				available_blobs.erase(blob_name);
			}

			// Figure out this layer's output
			for (int j = 0; j < layer_param.top_size(); ++j) {
				const string& blob_name = layer_param.top(j);
				
				// Check if we are doing in-place computation
				if (layer_param.bottom_size() > j &&
					blob_name == layer_param.bottom(j)) {
						// In-place computation
						LOG(INFO) << layer_param.name() << " -> " << blob_name << " (in-place)";
						in_place = true;
						available_blobs.insert(blob_name);
						top_vecs_[i].push_back(
							blobs_[blob_name_to_idx[blob_name]].get());
						top_id_vecs_[i].push_back(blob_name_to_idx[blob_name]);
				} else if (blob_name_to_idx.find(blob_name) != blob_name_to_idx.end()) {
					// If we are not doing in-place computation but has duplicated blobs,
					// raise an error.
					LOG(FATAL) << "Duplicate blobs produced by multiple sources.";
				} else {
					// Normal output.
					LOG(INFO) << layer_param.name() << " -> " << blob_name;
					shared_ptr<Blob<Dtype> > blob_pointer(new Blob<Dtype>());
					blobs_.push_back(blob_pointer);
					blob_names_.push_back(blob_name);
					blob_need_backward_.push_back(param.force_backward());
					blob_name_to_idx[blob_name] = blob_names_.size() - 1;
					available_blobs.insert(blob_name);
					top_vecs_[i].push_back(blobs_[blob_names_.size() - 1].get());
					top_id_vecs_[i].push_back(blob_names_.size() - 1);
				}
			}
			
			// After this layer is connected, set it up.
			//LOG(INFO) << "Setting up " << layer_names_[i];
			layers_[i]->SetUp(bottom_vecs_[i], &(top_vecs_[i]));
//.........这里部分代码省略.........

void Net<Dtype>::Init(const NetParameter& param) {
  // Basically, build all the layers and set up its connections.
  name_ = param.name();
  map<string, int> blob_name_to_idx;
  set<string> available_blobs;
  int num_layers = param.layers_size();
  CHECK_EQ(param.input_size() * 4, param.input_dim_size())
      << "Incorrect bottom blob dimension specifications.";
  // set the input blobs
  for (int i = 0; i < param.input_size(); ++i) {
    const string& blob_name = param.input(i);
    shared_ptr<Blob<Dtype> > blob_pointer(
        new Blob<Dtype>(param.input_dim(i * 4),
                        param.input_dim(i * 4 + 1),
                        param.input_dim(i * 4 + 2),
                        param.input_dim(i * 4 + 3)));
    blobs_.push_back(blob_pointer);
    blob_names_.push_back(blob_name);
    blob_need_backward_.push_back(param.force_backward());
    net_input_blob_indices_.push_back(i);
    net_input_blobs_.push_back(blob_pointer.get());
    blob_name_to_idx[blob_name] = i;
    available_blobs.insert(blob_name);
  }
  // For each layer, set up their input and output
  bottom_vecs_.resize(param.layers_size());
  top_vecs_.resize(param.layers_size());
  bottom_id_vecs_.resize(param.layers_size());
  top_id_vecs_.resize(param.layers_size());
  for (int i = 0; i < param.layers_size(); ++i) {
    const LayerConnection& layer_connection = param.layers(i);
    const LayerParameter& layer_param = layer_connection.layer();
    layers_.push_back(shared_ptr<Layer<Dtype> >(GetLayer<Dtype>(layer_param)));
    layer_names_.push_back(layer_param.name());
    LOG(INFO) << "Creating Layer " << layer_param.name();
    bool need_backward = param.force_backward();
    // Figure out this layer's input and output
    for (int j = 0; j < layer_connection.bottom_size(); ++j) {
      const string& blob_name = layer_connection.bottom(j);
      const int blob_id = blob_name_to_idx[blob_name];
      if (available_blobs.find(blob_name) == available_blobs.end()) {
        LOG(FATAL) << "Unknown blob input " << blob_name <<
            " to layer" << j;
      }
      LOG(INFO) << layer_param.name() << " <- " << blob_name;
      bottom_vecs_[i].push_back(
          blobs_[blob_id].get());
      bottom_id_vecs_[i].push_back(blob_id);
      // If a blob needs backward, this layer should provide it.
      need_backward |= blob_need_backward_[blob_id];
      available_blobs.erase(blob_name);
    }
    for (int j = 0; j < layer_connection.top_size(); ++j) {
      const string& blob_name = layer_connection.top(j);
      // Check if we are doing in-place computation
      if (layer_connection.bottom_size() > j &&
          blob_name == layer_connection.bottom(j)) {
        // In-place computation
        LOG(INFO) << layer_param.name() << " -> " << blob_name << " (in-place)";
        available_blobs.insert(blob_name);
        top_vecs_[i].push_back(
            blobs_[blob_name_to_idx[blob_name]].get());
        top_id_vecs_[i].push_back(blob_name_to_idx[blob_name]);
      } else if (blob_name_to_idx.find(blob_name) != blob_name_to_idx.end()) {
        // If we are not doing in-place computation but has duplicated blobs,
        // raise an error.
        LOG(FATAL) << "Duplicate blobs produced by multiple sources.";
      } else {
        // Normal output.
        LOG(INFO) << layer_param.name() << " -> " << blob_name;
        shared_ptr<Blob<Dtype> > blob_pointer(new Blob<Dtype>());
        blobs_.push_back(blob_pointer);
        blob_names_.push_back(blob_name);
        blob_need_backward_.push_back(param.force_backward());
        blob_name_to_idx[blob_name] = blob_names_.size() - 1;
        available_blobs.insert(blob_name);
        top_vecs_[i].push_back(blobs_[blob_names_.size() - 1].get());
        top_id_vecs_[i].push_back(blob_names_.size() - 1);
      }
    }
    // After this layer is connected, set it up.
    // LOG(INFO) << "Setting up " << layer_names_[i];
    layers_[i]->SetUp(bottom_vecs_[i], &top_vecs_[i]);
    for (int topid = 0; topid < top_vecs_[i].size(); ++topid) {
      LOG(INFO) << "Top shape: " << top_vecs_[i][topid]->channels() << " "
          << top_vecs_[i][topid]->height() << " "
          << top_vecs_[i][topid]->width();
    }
    // Check if this layer needs backward operation itself
    for (int j = 0; j < layers_[i]->layer_param().blobs_lr_size(); ++j) {
      need_backward |= (layers_[i]->layer_param().blobs_lr(j) > 0);
    }
    // Finally, set the backward flag
    layer_need_backward_.push_back(need_backward);
    if (need_backward) {
      LOG(INFO) << layer_names_[i] << " needs backward computation.";
      for (int j = 0; j < top_id_vecs_[i].size(); ++j) {
        blob_need_backward_[top_id_vecs_[i][j]] = true;
      }
    } else {
//.........这里部分代码省略.........