Case 1
Framework: Tensorflow 2.5.0, Intel-Tensorflow 2.5.0
Environment: Google Colab
I have a successfully quantized model quantized by LPOT that is to be run for inference without using LPOT API, so I wrote the following inference code:
with tf.compat.v1.Session() as sess:
tf.compat.v1.saved_model.loader.load(sess, ['serve'], model)
output = sess.graph.get_tensor_by_name(output_tensor_name)
predictions = sess.run(output, {input_tensor_name: x})
mse = tf.reduce_mean(tf.keras.losses.mean_squared_error(y, predictions))
print(mse.eval())
When running the line predictions = sess.run(output, {input_tensor_name: x}):
---------------------------------------------------------------------------
InternalError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1374 try:
-> 1375 return fn(*args)
1376 except errors.OpError as e:
7 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1359 return self._call_tf_sessionrun(options, feed_dict, fetch_list,
-> 1360 target_list, run_metadata)
1361
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1452 fetch_list, target_list,
-> 1453 run_metadata)
1454
InternalError: Missing 0-th output from {{node model/layer_1/Conv2D_eightbit_requantize}}
During handling of the above exception, another exception occurred:
InternalError Traceback (most recent call last)
<ipython-input-6-2bddd853d111> in <module>()
2 tf.compat.v1.saved_model.loader.load(sess, ['serve'], model)
3 output = sess.graph.get_tensor_by_name(output_tensor_name)
----> 4 predictions = sess.run(output, {input_tensor_name: x[:64]}) # 64, 257, 60, 1
5 mse = tf.reduce_mean(tf.keras.losses.mean_squared_error(y[:64], predictions))
6 print(mse.eval())
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
966 try:
967 result = self._run(None, fetches, feed_dict, options_ptr,
--> 968 run_metadata_ptr)
969 if run_metadata:
970 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1189 if final_fetches or final_targets or (handle and feed_dict_tensor):
1190 results = self._do_run(handle, final_targets, final_fetches,
-> 1191 feed_dict_tensor, options, run_metadata)
1192 else:
1193 results = []
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1367 if handle is None:
1368 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1369 run_metadata)
1370 else:
1371 return self._do_call(_prun_fn, handle, feeds, fetches)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1392 '\nsession_config.graph_options.rewrite_options.'
1393 'disable_meta_optimizer = True')
-> 1394 raise type(e)(node_def, op, message)
1395
1396 def _extend_graph(self):
InternalError: Missing 0-th output from node model/layer_1/Conv2D_eightbit_requantize (defined at <ipython-input-6-2bddd853d111>:2)
This error happens with or without Intel-Tensorflow==2.5.0 installed, nor is it resolved when os.environ['TF_ENABLE_ONEDNN_OPTS'] = '1' is set explicitly.
On the other hand, when I run the same code in VS Code with Python 3.6.8 64-bit base: Conda, it returns the same error message as in Case 2.
Case 2
Framework: Tensorflow 2.4.0, Intel-Tensorflow 2.4.0
Environment: Google Colab
This case works well and prints out the MSE loss of the predictions, but when I uninstall Intel-Tensorflow 2.4.0 and run with official Tensorflow only, while running the same line in Case 1 (predictions = sess.run(output, {input_tensor_name: x})):
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1374 try:
-> 1375 return fn(*args)
1376 except errors.OpError as e:
7 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1357 # Ensure any changes to the graph are reflected in the runtime.
-> 1358 self._extend_graph()
1359 return self._call_tf_sessionrun(options, feed_dict, fetch_list,
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _extend_graph(self)
1397 with self._graph._session_run_lock(): # pylint: disable=protected-access
-> 1398 tf_session.ExtendSession(self._session)
1399
InvalidArgumentError: No OpKernel was registered to support Op 'QuantizedMatMulWithBiasAndDequantize' used by {{node model/dense/Tensordot/MatMul_eightbit_requantize}} with these attrs: [input_quant_mode="MIN_FIRST", T1=DT_QUINT8, Toutput=DT_FLOAT, T2=DT_QINT8, Tbias=DT_QINT32, transpose_a=false, transpose_b=false]
Registered devices: [CPU]
Registered kernels:
<no registered kernels>
[[model/dense/Tensordot/MatMul_eightbit_requantize]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-6-2bddd853d111> in <module>()
2 tf.compat.v1.saved_model.loader.load(sess, ['serve'], model)
3 output = sess.graph.get_tensor_by_name(output_tensor_name)
----> 4 predictions = sess.run(output, {input_tensor_name: x[:64]}) # 64, 257, 60, 1
5 mse = tf.reduce_mean(tf.keras.losses.mean_squared_error(y[:64], predictions))
6 print(mse.eval())
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
966 try:
967 result = self._run(None, fetches, feed_dict, options_ptr,
--> 968 run_metadata_ptr)
969 if run_metadata:
970 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1189 if final_fetches or final_targets or (handle and feed_dict_tensor):
1190 results = self._do_run(handle, final_targets, final_fetches,
-> 1191 feed_dict_tensor, options, run_metadata)
1192 else:
1193 results = []
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1367 if handle is None:
1368 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1369 run_metadata)
1370 else:
1371 return self._do_call(_prun_fn, handle, feeds, fetches)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1392 '\nsession_config.graph_options.rewrite_options.'
1393 'disable_meta_optimizer = True')
-> 1394 raise type(e)(node_def, op, message)
1395
1396 def _extend_graph(self):
InvalidArgumentError: No OpKernel was registered to support Op 'QuantizedMatMulWithBiasAndDequantize' used by node model/dense/Tensordot/MatMul_eightbit_requantize (defined at <ipython-input-6-2bddd853d111>:2) with these attrs: [input_quant_mode="MIN_FIRST", T1=DT_QUINT8, Toutput=DT_FLOAT, T2=DT_QINT8, Tbias=DT_QINT32, transpose_a=false, transpose_b=false]
Registered devices: [CPU]
Registered kernels:
<no registered kernels>
[[model/dense/Tensordot/MatMul_eightbit_requantize]]
The error persists even with os.environ['TF_ENABLE_ONEDNN_OPTS'] = '1' set explicitly.
Conclusion
I believe both cases are caused by the same type of error, i.e. No OpKernel was registered to support Op ...
I was given to understand that with official Tensorflow v2.5 installed and the environment variable TF_ENABLE_ONEDNN_OPTS=1 set (reference), the quantized model is supposed to run with oneDNN supported. But it doesn't seem to be the case in neither v2.4 nor v2.5.
My question is how do I have official Tensorflow 2.5 environment with oneDNN support without having to install Intel-Tensorflow? Or why does Intel-Tensorflow 2.5 not work? Thanks.
