Hello,
My code :
i’m beginner with tensorflow, and i’m trying to make a deeplab implementation in tensorflow 2.
I run my notebook and i don’t have error during the fit when i use run_eagerly = True, but with this option the loss stay at nan
And when i don’t use run_eagerly, i have this error :
————————————————————————— ValueError Traceback (most recent call last) <ipython-input-16-f5ffc11fb617> in <module> 133 dataset_entrain = dataset_entrain.shuffle(buffer_size=10).batch(batch_size=1) 134 –> 135 model.fit(dataset_entrain, epochs=10, callbacks=[ModelCheckpoint(‘policy_seg_{epoch}.h5’)]) 136 137 ~/envs/project/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) 1098 _r=1): 1099 callbacks.on_train_batch_begin(step) -> 1100 tmp_logs = self.train_function(iterator) 1101 if data_handler.should_sync: 1102 context.async_wait() ~/envs/project/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds) 826 tracing_count = self.experimental_get_tracing_count() 827 with trace.Trace(self._name) as tm: –> 828 result = self._call(*args, **kwds) 829 compiler = “xla” if self._experimental_compile else “nonXla” 830 new_tracing_count = self.experimental_get_tracing_count() ~/envs/project/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in _call(self, *args, **kwds) 886 # Lifting succeeded, so variables are initialized and we can run the 887 # stateless function. –> 888 return self._stateless_fn(*args, **kwds) 889 else: 890 _, _, _, filtered_flat_args = ~/envs/project/lib/python3.8/site-packages/tensorflow/python/eager/function.py in __call__(self, *args, **kwargs) 2939 with self._lock: 2940 (graph_function, -> 2941 filtered_flat_args) = self._maybe_define_function(args, kwargs) 2942 return graph_function._call_flat( 2943 filtered_flat_args, captured_inputs=graph_function.captured_inputs) # pylint: disable=protected-access ~/envs/project/lib/python3.8/site-packages/tensorflow/python/eager/function.py in _maybe_define_function(self, args, kwargs) 3359 3360 self._function_cache.missed.add(call_context_key) -> 3361 graph_function = self._create_graph_function(args, kwargs) 3362 self._function_cache.primary[cache_key] = graph_function 3363 ~/envs/project/lib/python3.8/site-packages/tensorflow/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes) 3194 arg_names = base_arg_names + missing_arg_names 3195 graph_function = ConcreteFunction( -> 3196 func_graph_module.func_graph_from_py_func( 3197 self._name, 3198 self._python_function, ~/envs/project/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes) 988 _, original_func = tf_decorator.unwrap(python_func) 989 –> 990 func_outputs = python_func(*func_args, **func_kwargs) 991 992 # invariant: `func_outputs` contains only Tensors, CompositeTensors, ~/envs/project/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in wrapped_fn(*args, **kwds) 632 xla_context.Exit() 633 else: –> 634 out = weak_wrapped_fn().__wrapped__(*args, **kwds) 635 return out 636 ~/envs/project/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs) 975 except Exception as e: # pylint:disable=broad-except 976 if hasattr(e, “ag_error_metadata”): –> 977 raise e.ag_error_metadata.to_exception(e) 978 else: 979 raise ValueError: in user code: /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:805 train_function * return step_function(self, iterator) /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:795 step_function ** outputs = model.distribute_strategy.run(run_step, args=(data,)) /envs/project/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:1259 run return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:2730 call_for_each_replica return self._call_for_each_replica(fn, args, kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:3417 _call_for_each_replica return fn(*args, **kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:788 run_step ** outputs = model.train_step(data) /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:754 train_step y_pred = self(x, training=True) /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py:1012 __call__ outputs = call_fn(inputs, *args, **kwargs) <ipython-input-16-f5ffc11fb617>:83 call ** x = keras.layers.Conv2D(64, 7, strides=2, padding=”same”)(inputs) /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py:1008 __call__ self._maybe_build(inputs) /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py:2710 _maybe_build self.build(input_shapes) # pylint:disable=not-callable /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/layers/convolutional.py:198 build self.kernel = self.add_weight( /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py:623 add_weight variable = self._add_variable_with_custom_getter( /envs/project/lib/python3.8/site-packages/tensorflow/python/training/tracking/base.py:805 _add_variable_with_custom_getter new_variable = getter( /envs/project/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer_utils.py:130 make_variable return tf_variables.VariableV1( /envs/project/lib/python3.8/site-packages/tensorflow/python/ops/variables.py:260 __call__ return cls._variable_v1_call(*args, **kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/ops/variables.py:206 _variable_v1_call return previous_getter( /envs/project/lib/python3.8/site-packages/tensorflow/python/ops/variables.py:67 getter return captured_getter(captured_previous, **kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:3332 creator return next_creator(**kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/ops/variables.py:67 getter return captured_getter(captured_previous, **kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:3332 creator return next_creator(**kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/ops/variables.py:67 getter return captured_getter(captured_previous, **kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:3332 creator return next_creator(**kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/ops/variables.py:67 getter return captured_getter(captured_previous, **kwargs) /envs/project/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py:730 invalid_creator_scope raise ValueError( ValueError: tf.function-decorated function tried to create variables on non-first call.
You can find my code in the link https://gofile.io/d/mTlna9 , what can i do to debug my code ?
Thank you for your advice
submitted by /u/Tensor_Beginner
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