I get this error and I was checking possible mistakes for a while. Any idea?
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-20-1e9a8b263fca> in <module>
13
14 # Run the component
---> 15 context.run(transform)
16 ### END CODE HERE
/opt/conda/lib/python3.8/site-packages/tfx/orchestration/experimental/interactive/interactive_context.py in run_if_ipython(*args, **kwargs)
65 # __IPYTHON__ variable is set by IPython, see
66 # https://ipython.org/ipython-doc/rel-0.10.2/html/interactive/reference.html#embedding-ipython.
---> 67 return fn(*args, **kwargs)
68 else:
69 absl.logging.warning(
/opt/conda/lib/python3.8/site-packages/tfx/orchestration/experimental/interactive/interactive_context.py in run(self, component, enable_cache, beam_pipeline_args)
180 telemetry_utils.LABEL_TFX_RUNNER: runner_label,
181 }):
--> 182 execution_id = launcher.launch().execution_id
183
184 return execution_result.ExecutionResult(
/opt/conda/lib/python3.8/site-packages/tfx/orchestration/launcher/base_component_launcher.py in launch(self)
200 absl.logging.info('Running executor for %s',
201 self._component_info.component_id)
--> 202 self._run_executor(execution_decision.execution_id,
203 execution_decision.input_dict,
204 execution_decision.output_dict,
/opt/conda/lib/python3.8/site-packages/tfx/orchestration/launcher/in_process_component_launcher.py in _run_executor(self, execution_id, input_dict, output_dict, exec_properties)
65 executor_context) # type: ignore
66
---> 67 executor.Do(input_dict, output_dict, exec_properties)
/opt/conda/lib/python3.8/site-packages/tfx/components/transform/executor.py in Do(self, input_dict, output_dict, exec_properties)
415 label_outputs[labels.CACHE_OUTPUT_PATH_LABEL] = cache_output
416 status_file = 'status_file' # Unused
--> 417 self.Transform(label_inputs, label_outputs, status_file)
418 absl.logging.debug('Cleaning up temp path %s on executor success',
419 temp_path)
/opt/conda/lib/python3.8/site-packages/tfx/components/transform/executor.py in Transform(***failed resolving arguments***)
933 materialization_format = (
934 transform_paths_file_formats[-1] if materialize_output_paths else None)
--> 935 self._RunBeamImpl(analyze_data_list, transform_data_list,
936 preprocessing_fn, input_dataset_metadata,
937 transform_output_path, raw_examples_data_format,
/opt/conda/lib/python3.8/site-packages/tfx/components/transform/executor.py in _RunBeamImpl(self, analyze_data_list, transform_data_list, preprocessing_fn, input_dataset_metadata, transform_output_path, raw_examples_data_format, temp_path, input_cache_dir, output_cache_dir, compute_statistics, per_set_stats_output_paths, materialization_format, analyze_paths_count)
980 analyze_input_columns = tft.get_analyze_input_columns(
981 preprocessing_fn, unprojected_typespecs)
--> 982 transform_input_columns = tft.get_transform_input_columns(
983 preprocessing_fn, unprojected_typespecs)
984 # Use the same dataset (same columns) for AnalyzeDataset and computing
/opt/conda/lib/python3.8/site-packages/tensorflow_transform/inspect_preprocessing_fn.py in get_transform_input_columns(preprocessing_fn, specs)
83 specs)
84 output_signature = preprocessing_fn(input_signature.copy())
---> 85 transform_input_tensors = graph_tools.get_dependent_inputs(
86 graph, input_signature, output_signature)
87 return list(transform_input_tensors.keys())
/opt/conda/lib/python3.8/site-packages/tensorflow_transform/graph_tools.py in get_dependent_inputs(graph, input_tensors, output_tensors)
775 dependent_inputs = {}
776 for output_tensor in output_iterator:
--> 777 dependent_inputs.update(graph_analyzer.get_dependent_inputs(output_tensor))
778 return {
779 name: tensor
/opt/conda/lib/python3.8/site-packages/tensorflow_transform/graph_tools.py in wrapper(self, tensor_or_op)
166 """Wrapper when calling func to re-raise exceptions."""
167 try:
--> 168 return func(self, tensor_or_op)
169 except _UnexpectedPlaceholderError as e:
170 if e.func_graph_name:
/opt/conda/lib/python3.8/site-packages/tensorflow_transform/graph_tools.py in get_dependent_inputs(self, tensor_or_op)
722 tensor_or_op,
723 (tf.Tensor, tf.SparseTensor, tf.RaggedTensor, tf.Operation)):
--> 724 raise TypeError(
725 'Expected Tensor, SparseTensor, RaggedTensor or Operation got {} of '
726 'type {}'.format(tensor_or_op, type(tensor_or_op)))
TypeError: Expected Tensor, SparseTensor, RaggedTensor or Operation got None of type <class 'NoneType'>
The code I tried to perform looks like this:
Exercise 6
Exercise 7
