I have installed tensorflow-macos and tensorflow-metal on Big Sur on a iMac 27" with AMD Radeon Pro 5700 XT.
I am trying to run Keras code from Francios Challet's Deep Learning example: E.g Chapter 11-part04_sequence-to-Sequence
seq2seq_rnn.compile(
optimizer="rmsprop",
loss="sparse_categorical_crossentropy",
metrics=["accuracy"])
seq2seq_rnn.fit(train_ds, epochs=15, validation_data=val_ds)
2021-07-15 13:17:00.117869: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:112] Plugin optimizer for device_type GPU is enabled.
2021-07-15 13:17:01.403133: W tensorflow/core/framework/op_kernel.cc:1767] OP_REQUIRES failed at partitioned_function_ops.cc:114 : Invalid argument: No OpKernel was registered to support Op 'CudnnRNNV3' used by {{node cond_41/then/_0/cond/CudnnRNNV3}} with these attrs: [T=DT_FLOAT, input_mode="linear_input", direction="unidirectional", rnn_mode="gru", seed2=0, is_training=true, num_proj=0, time_major=false, seed=0, dropout=0]
Registered devices: [CPU, GPU]
Registered kernels:
<no registered kernels>
[[cond_41/then/_0/cond/CudnnRNNV3]]
2021-07-15 13:17:01.419061: W tensorflow/core/framework/op_kernel.cc:1767] OP_REQUIRES failed at partitioned_function_ops.cc:114 : Invalid argument: No OpKernel was registered to support Op 'CudnnRNNV3' used by {{node cond_41/then/_0/cond/CudnnRNNV3}} with these attrs: [time_major=false, dropout=0, seed=0, T=DT_FLOAT, input_mode="linear_input", direction="unidirectional", rnn_mode="gru", seed2=0, is_training=true, num_proj=0]
Registered devices: [CPU, GPU]
Registered kernels:
<no registered kernels>
[[cond_41/then/_0/cond/CudnnRNNV3]]
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/var/folders/3n/56fpv14n4wj0c1l1sb106pzw0000gn/T/ipykernel_94493/3093225856.py in <module>
3 loss="sparse_categorical_crossentropy",
4 metrics=["accuracy"])
----> 5 seq2seq_rnn.fit(train_ds, epochs=15, validation_data=val_ds)
~/tensorflow-metal/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
1181 _r=1):
1182 callbacks.on_train_batch_begin(step)
-> 1183 tmp_logs = self.train_function(iterator)
1184 if data_handler.should_sync:
1185 context.async_wait()
~/tensorflow-metal/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
887
888 with OptionalXlaContext(self._jit_compile):
--> 889 result = self._call(*args, **kwds)
890
891 new_tracing_count = self.experimental_get_tracing_count()
~/tensorflow-metal/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in _call(self, *args, **kwds)
948 # Lifting succeeded, so variables are initialized and we can run the
949 # stateless function.
--> 950 return self._stateless_fn(*args, **kwds)
951 else:
952 _, _, _, filtered_flat_args = \
~/tensorflow-metal/lib/python3.8/site-packages/tensorflow/python/eager/function.py in __call__(self, *args, **kwargs)
3021 (graph_function,
3022 filtered_flat_args) = self._maybe_define_function(args, kwargs)
-> 3023 return graph_function._call_flat(
3024 filtered_flat_args, captured_inputs=graph_function.captured_inputs) # pylint: disable=protected-access
3025
~/tensorflow-metal/lib/python3.8/site-packages/tensorflow/python/eager/function.py in _call_flat(self, args, captured_inputs, cancellation_manager)
1958 and executing_eagerly):
1959 # No tape is watching; skip to running the function.
-> 1960 return self._build_call_outputs(self._inference_function.call(
1961 ctx, args, cancellation_manager=cancellation_manager))
1962 forward_backward = self._select_forward_and_backward_functions(
~/tensorflow-metal/lib/python3.8/site-packages/tensorflow/python/eager/function.py in call(self, ctx, args, cancellation_manager)
589 with _InterpolateFunctionError(self):
590 if cancellation_manager is None:
--> 591 outputs = execute.execute(
592 str(self.signature.name),
593 num_outputs=self._num_outputs,
~/tensorflow-metal/lib/python3.8/site-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
57 try:
58 ctx.ensure_initialized()
---> 59 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
60 inputs, attrs, num_outputs)
61 except core._NotOkStatusException as e:
InvalidArgumentError: 2 root error(s) found.
(0) Invalid argument: No OpKernel was registered to support Op 'CudnnRNNV3' used by {{node cond_41/then/_0/cond/CudnnRNNV3}} with these attrs: [T=DT_FLOAT, input_mode="linear_input", direction="unidirectional", rnn_mode="gru", seed2=0, is_training=true, num_proj=0, time_major=false, seed=0, dropout=0]
Registered devices: [CPU, GPU]
Registered kernels:
<no registered kernels>
[[cond_41/then/_0/cond/CudnnRNNV3]]
[[model/bidirectional/backward_gru/PartitionedCall]]
[[broadcast_weights_1/assert_broadcastable/is_valid_shape/else/_1/broadcast_weights_1/assert_broadcastable/is_valid_shape/has_valid_nonscalar_shape/then/_53/broadcast_weights_1/assert_broadcastable/is_valid_shape/has_valid_nonscalar_shape/has_invalid_dims/concat/_66]]
(1) Invalid argument: No OpKernel was registered to support Op 'CudnnRNNV3' used by {{node cond_41/then/_0/cond/CudnnRNNV3}} with these attrs: [T=DT_FLOAT, input_mode="linear_input", direction="unidirectional", rnn_mode="gru", seed2=0, is_training=true, num_proj=0, time_major=false, seed=0, dropout=0]
Registered devices: [CPU, GPU]
Registered kernels:
<no registered kernels>
[[cond_41/then/_0/cond/CudnnRNNV3]]
[[model/bidirectional/backward_gru/PartitionedCall]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_520769]
Function call stack:
train_function -> train_function
