I have trained and saved a model in lunx/ubuntu. Now when i tried to run it on windows, it throw following error
InvalidArgument Traceback (most recent call last)
Input In [19], in <cell line: 12>()
9 return tokenizer(ex["sentence"])
11 tokenized_ds = ds.map(partial(preprocess_fn, tokenizer=quantizer.tokenizer))
---> 12 ort_outputs = ort_model.evaluation_loop(tokenized_ds)
13 # Extract logits!
14 pred=ort_outputs.predictions
File e:\fiverr\upwork\venv\lib\site-packages\optimum\onnxruntime\model.py:98, in ORTModel.evaluation_loop(self, dataset)
96 labels = None
97 onnx_inputs = {key: np.array([inputs[key]]) for key in self.onnx_config.inputs if key in inputs}
---> 98 preds = session.run(self.onnx_named_outputs, onnx_inputs)
99 if len(preds) == 1:
100 preds = preds[0]
File e:\fiverr\upwork\venv\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py:192, in Session.run(self, output_names, input_feed, run_options)
190 output_names = [output.name for output in self._outputs_meta]
191 try:
--> 192 return self._sess.run(output_names, input_feed, run_options)
193 except C.EPFail as err:
194 if self._enable_fallback:
InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Unexpected input data type. Actual: (tensor(int32)) , expected: (tensor(int64))
Code is as follow and working on linux
# %%time
from time import time
start=time()
# Create a dataset or load one from the Hub
ds = Dataset.from_dict({"sentence": list(val_df.tweet)})
# Tokenize the inputs
def preprocess_fn(ex, tokenizer):
return tokenizer(ex["sentence"])
tokenized_ds = ds.map(partial(preprocess_fn, tokenizer=quantizer.tokenizer))
ort_outputs = ort_model.evaluation_loop(tokenized_ds)
# Extract logits!
pred=ort_outputs.predictions
end=time()
total_time=end-start
print(total_time)