bigdl.contrib.onnx package

Submodules

bigdl.contrib.onnx.converter_utils module

bigdl.contrib.onnx.converter_utils.calc_output_shape(input, kernel, padding=0, stride=1, dilation=1, ceil_mode=False)

bigdl.contrib.onnx.converter_utils.parse_node_attr(node_proto)

bigdl.contrib.onnx.converter_utils.parse_tensor_data(tensor_proto)

bigdl.contrib.onnx.onnx_loader module

class bigdl.contrib.onnx.onnx_loader.OnnxLoader

Bases: object

load_graph(graph_proto)

load_model(file_path)

bigdl.contrib.onnx.onnx_loader.load(model_path)

bigdl.contrib.onnx.onnx_loader.load_model_proto(model_proto)

bigdl.contrib.onnx.ops_converter module

bigdl.contrib.onnx.ops_converter.average_pool(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.batch_norm(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.concat(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.constant(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.conv(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.gather(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.gemm(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.max_pool(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.relu(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.reshape(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.shape(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.softmax(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_converter.unsqueeze(inputs, prev_modules, attrs, outputs)

bigdl.contrib.onnx.ops_mapping module

Operator attributes conversion

Module contents