import torch
import onnx
import tensorflow as tf
import onnx_tf
from torchvision.models import resnet50
# 加载PyTorch的ResNet50模型
pytorch_model = resnet50(pretrained=True)
pytorch_model.eval()
# 将PyTorch模型导出为ONNX格式
input_shape = (1, 3, 224, 224)
dummy_input = torch.randn(input_shape)
onnx_model_path = 'resnet50.onnx'
torch.onnx.export(pytorch_model, dummy_input, onnx_model_path, opset_version=12, verbose=False)
# 加载ONNX模型
onnx_model = onnx.load(onnx_model_path)
# 将ONNX模型转换为TensorFlow格式
tf_model_path = 'resnet50.pb'
onnx_model = onnx.load(onnx_model_path)
from onnx_tf.backend import prepare
tf_rep = prepare(onnx_model)
tf_rep.export_graph(tf_model_path)    # 错误

警告：`input.1`不是有效的tf.function参数名。正在更改为`input_1`。
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-4-f35b83c104b8> in <cell line: 8>()
      6 tf_model_path = 'resnet50'
      7 tf_rep = prepare(onnx_model)
----> 8 tf_rep.export_graph(tf_model_path)
...

<details>
<summary>英文:</summary>
I am trying to convert a `onnx` model to `tflite`, im facing an error executing line `tf_rep.export_graph(tf_model_path)`. This question was asked in SO before but none provided a definitive solution.
Requirements installed: `tensorflow: 2.12.0`, `onnx 1.14.0`, `onnx-tf 1.10.0`, `Python 3.10.12`
      
      import torch
      import onnx
      import tensorflow as tf
      import onnx_tf
      from torchvision.models import resnet50
      # Load the PyTorch ResNet50 model
      pytorch_model = resnet50(pretrained=True)
      pytorch_model.eval()
      # Export the PyTorch model to ONNX format
      input_shape = (1, 3, 224, 224)
      dummy_input = torch.randn(input_shape)
      onnx_model_path = &#39;resnet50.onnx&#39;
      torch.onnx.export(pytorch_model, dummy_input, onnx_model_path, opset_version=12, verbose=False)
      # Load the ONNX model
      onnx_model = onnx.load(onnx_model_path)
      # Convert the ONNX model to TensorFlow format
      tf_model_path = &#39;resnet50.pb
      onnx_model = onnx.load(onnx_model_path)
      from onnx_tf.backend import prepare
      tf_rep = prepare(onnx_model)
      tf_rep.export_graph(tf_model_path)    #ERROR
Error:
    WARNING:absl:`input.1` is not a valid tf.function parameter name. Sanitizing to `input_1`.
    ---------------------------------------------------------------------------
    KeyError                                  Traceback (most recent call last)
    &lt;ipython-input-4-f35b83c104b8&gt; in &lt;cell line: 8&gt;()
        6 tf_model_path = &#39;resnet50&#39;
        7 tf_rep = prepare(onnx_model)
    ----&gt; 8 tf_rep.export_graph(tf_model_path)
    35 frames
    /usr/local/lib/python3.10/dist-packages/onnx_tf/handlers/backend/conv_mixin.py in tf__conv(cls, node, input_dict, transpose)
        17                 do_return = False
        18                 retval_ = ag__.UndefinedReturnValue()
    ---&gt; 19                 x = ag__.ld(input_dict)[ag__.ld(node).inputs[0]]
        20                 x_rank = ag__.converted_call(ag__.ld(len), (ag__.converted_call(ag__.ld(x).get_shape, (), None, fscope),), None, fscope)
        21                 x_shape = ag__.converted_call(ag__.ld(tf_shape), (ag__.ld(x), ag__.ld(tf).int32), None, fscope)
    KeyError: in user code:
        File &quot;/usr/local/lib/python3.10/dist-packages/onnx_tf/backend_tf_module.py&quot;, line 99, in __call__  *
            output_ops = self.backend._onnx_node_to_tensorflow_op(onnx_node,
        File &quot;/usr/local/lib/python3.10/dist-packages/onnx_tf/backend.py&quot;, line 347, in _onnx_node_to_tensorflow_op  *
            return handler.handle(node, tensor_dict=tensor_dict, strict=strict)
        File &quot;/usr/local/lib/python3.10/dist-packages/onnx_tf/handlers/handler.py&quot;, line 59, in handle  *
            return ver_handle(node, **kwargs)
        File &quot;/usr/local/lib/python3.10/dist-packages/onnx_tf/handlers/backend/conv.py&quot;, line 15, in version_11  *
            return cls.conv(node, kwargs[&quot;tensor_dict&quot;])
        File &quot;/usr/local/lib/python3.10/dist-packages/onnx_tf/handlers/backend/conv_mixin.py&quot;, line 29, in conv  *
            x = input_dict[node.inputs[0]]
        KeyError: &#39;input.1&#39;
</details>
# 答案1
**得分**: 2
The problem was with a parameter name in `onnx` model.
```python
import onnx
onnx_model = onnx.load(onnx_model_path)
print("Model Inputs: ", [inp.name for inp in onnx_model.graph.input])

import onnx
from onnx import helper
onnx_model = onnx.load(onnx_model_path)
# Define a mapping from old names to new names
name_map = {"input.1": "input_1"}
# Initialize a list to hold the new inputs
new_inputs = []
# Iterate over the inputs and change their names if needed
for inp in onnx_model.graph.input:
    if inp.name in name_map:
        # Create a new ValueInfoProto with the new name
        new_inp = helper.make_tensor_value_info(name_map[inp.name],
                                                inp.type.tensor_type.elem_type,
                                                [dim.dim_value for dim in inp.type.tensor_type.shape.dim])
        new_inputs.append(new_inp)
    else:
        new_inputs.append(inp)
# Clear the old inputs and add the new ones
onnx_model.graph.ClearField("input")
onnx_model.graph.input.extend(new_inputs)
# Go through all nodes in the model and replace the old input name with the new one
for node in onnx_model.graph.node:
    for i, input_name in enumerate(node.input):
        if input_name in name_map:
            node.input[i] = name_map[input_name]
# Save the renamed ONNX model
onnx.save(onnx_model, 'resnet50-new.onnx')

import onnx
onnx_model_path = 'resnet50-new.onnx'
onnx_model = onnx.load(onnx_model_path)
from onnx_tf.backend import prepare
tf_model_path = 'resnet50'
tf_rep = prepare(onnx_model)
tf_rep.export_graph(tf_model_path)