leandron opened a new issue #5774:
URL: https://github.com/apache/incubator-tvm/issues/5774
After #5682, we're now seeing the error below on
`test_forward_mediapipe_hand_landmark`. I think that it is not seen on upstream
CI because of file caching. As I ran this test, master points at
`c7274fd3b0f693fc6214a450e13d5e99026337ae`.
This is the error:
```
_____________________ test_forward_mediapipe_hand_landmark
_____________________
def test_forward_mediapipe_hand_landmark():
"""Test MediaPipe 2D hand landmark TF Lite model."""
# MediaPipe 2D hand landmark TF
tflite_model_file = download_testdata(
"https://github.com/google/mediapipe/raw/master/mediapipe/models/hand_landmark.tflite";,
"hand_landmark.tflite")
with open(tflite_model_file, "rb") as f:
tflite_model_buf = f.read()
data = np.random.uniform(size=(1, 256, 256, 3)).astype('float32')
tflite_output = run_tflite_graph(tflite_model_buf, data)
> tvm_output = run_tvm_graph(tflite_model_buf, data, 'input_1',
num_output=2)
tests/python/frontend/tflite/test_forward.py:2451:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
tests/python/frontend/tflite/test_forward.py:136: in run_tvm_graph
dtype_dict=dtype_dict)
python/tvm/relay/frontend/tflite.py:2712: in from_tflite
op_converter.convert_op_to_relay()
python/tvm/relay/frontend/tflite.py:185: in convert_op_to_relay
ret = self.convert_map[op_code_str](op)
python/tvm/relay/frontend/tflite.py:2454: in convert_dequantize
in_expr = self.get_expr(input_tensor.tensor_idx)
python/tvm/relay/frontend/tflite.py:2563: in get_expr
return self.exp_tab.get_expr(get_tensor_name(self.subgraph,
input_tensor_idx))
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
self = <tvm.relay.frontend.common.ExprTable object at 0x7f244ac74f28>
name = 'conv2d/Kernel'
def get_expr(self, name):
> return self.exprs[name]
E KeyError: 'conv2d/Kernel'
python/tvm/relay/frontend/common.py:294: KeyError
----------------------------- Captured stdout call
-----------------------------
```
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