| import onnx |
| |
| model = onnx.load('modelSRC/mModelEncoder.onnx') |
| output =[node.name for node in model.graph.output] |
| |
| input_all = [node.name for node in model.graph.input] |
| input_initializer = [node.name for node in model.graph.initializer] |
| net_feed_input = list(set(input_all) - set(input_initializer)) |
| |
| print('Encoder Inputs: ', net_feed_input) |
| print('Encoder Outputs: ', output) |
| print("") |
| |
| onnx.checker.check_model(model) |
| graph_def = model.graph |
| |
| inputs = graph_def.input |
| for graph_input in inputs: |
| input_shape = [] |
| for d in graph_input.type.tensor_type.shape.dim: |
| if d.dim_value == 0: |
| input_shape.append(None) |
| else: |
| input_shape.append(d.dim_value) |
| print( |
| f"Input Name: {graph_input.name}, Input Data Type: {graph_input.type.tensor_type.elem_type}, Input Shape: {input_shape}" |
| ) |
| |
| |
| print("") |
| outputs = graph_def.output |
| for graph_output in outputs: |
| output_shape = [] |
| for d in graph_output.type.tensor_type.shape.dim: |
| if d.dim_value == 0: |
| output_shape.append(None) |
| else: |
| output_shape.append(d.dim_value) |
| print( |
| f"Output Name: {graph_output.name}, Output Data Type: {graph_output.type.tensor_type.elem_type}, Output Shape: {output_shape}" |
| ) |
| |
| |
| model = onnx.load('modelSRC/mModelDecoder.onnx') |
| output =[node.name for node in model.graph.output] |
| |
| input_all = [node.name for node in model.graph.input] |
| input_initializer = [node.name for node in model.graph.initializer] |
| net_feed_input = list(set(input_all) - set(input_initializer)) |
| |
| print("\n") |
| |
| print('Decoder Inputs: ', net_feed_input) |
| print('Decoder Outputs: ', output) |
| print("") |
| |
| onnx.checker.check_model(model) |
| graph_def = model.graph |
| |
| inputs = graph_def.input |
| for graph_input in inputs: |
| input_shape = [] |
| for d in graph_input.type.tensor_type.shape.dim: |
| if d.dim_value == 0: |
| input_shape.append(None) |
| else: |
| input_shape.append(d.dim_value) |
| print( |
| f"Input Name: {graph_input.name}, Input Data Type: {graph_input.type.tensor_type.elem_type}, Input Shape: {input_shape}" |
| ) |
| |
| print("") |
| outputs = graph_def.output |
| for graph_output in outputs: |
| output_shape = [] |
| for d in graph_output.type.tensor_type.shape.dim: |
| if d.dim_value == 0: |
| output_shape.append(None) |
| else: |
| output_shape.append(d.dim_value) |
| print( |
| f"Output Name: {graph_output.name}, Output Data Type: {graph_output.type.tensor_type.elem_type}, Output Shape: {output_shape}" |
| ) |