Issues Encountered with STM32Cube AI Cloud Usage
I have built and trained a recursive model with my data and generated the `.h5` and `.tflite` files. While I have been able to optimize the `.h5` file successfully, I am facing difficulties quantizing it. Below is the error I receive when attempting quantization:
No data specified, enabling fake quantization
Converting original model to TFLite...
/app/quantizer/cli.py:53:1: error: 'tf.TensorListReserve' op requires element_shape to be static during TF Lite transformation pass
res = quantize_from_local_file(
^
<unknown>:0: note: loc(fused["StatefulPartitionedCall:", "StatefulPartitionedCall"]): called from
/app/quantizer/cli.py:53:1: error: failed to legalize operation 'tf.TensorListReserve' that was explicitly marked illegal
res = quantize_from_local_file(
^
<unknown>:0: note: loc(fused["StatefulPartitionedCall:", "StatefulPartitionedCall"]): called from
<unknown>:0: error: Lowering tensor list ops is failed. Please consider using Select TF ops and disabling `_experimental_lower_tensor_list_ops` flag in the TFLite converter object. For example, converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS]\n converter._experimental_lower_tensor_list_ops = False
2024-06-11 11:33:30.384275: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-06-11 11:33:30.412400: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-06-11 11:33:32.873971: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:378] Ignored output_format.
2024-06-11 11:33:32.874007: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:381] Ignored drop_control_dependency.
2024-06-11 11:33:32.874486: I tensorflow/cc/saved_model/reader.cc:83] Reading SavedModel from: /tmp/tmpkfrpccum
2024-06-11 11:33:32.876786: I tensorflow/cc/saved_model/reader.cc:51] Reading meta graph with tags { serve }
2024-06-11 11:33:32.876809: I tensorflow/cc/saved_model/reader.cc:146] Reading SavedModel debug info (if present) from: /tmp/tmpkfrpccum
2024-06-11 11:33:32.882099: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:388] MLIR V1 optimization pass is not enabled
2024-06-11 11:33:32.883401: I tensorflow/cc/saved_model/loader.cc:233] Restoring SavedModel bundle.
2024-06-11 11:33:32.941507: I tensorflow/cc/saved_model/loader.cc:217] Running initialization op on SavedModel bundle at path: /tmp/tmpkfrpccum
2024-06-11 11:33:32.957142: I tensorflow/cc/saved_model/loader.cc:316] SavedModel load for tags { serve }; Status: success: OK. Took 82657 microseconds.
2024-06-11 11:33:32.990057: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:269] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
loc(callsite(callsite(fused["TensorListReserve:", callsite("sequential/simple_rnn/TensorArrayV2_1@__inference__wrapped_model_444"("/app/quantizer/cli.py":53:1) at callsite("/app/quantizer/quantize.py":63:1 at callsite("/app/quantizer/quantize.py":114:1 at callsite("/app/quantizer/helpers.py":47:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1139:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1093:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1601:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1579:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/convert_phase.py":205:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1502:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/functional.py":460:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/training.py":4031:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/base_layer.py":3470:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/base_serialization.py":61:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/layer_serialization.py":79:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/layer_serialization.py":106:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/model_serialization.py":53:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/save_impl.py":234:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saving_utils.py":158:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saving_utils.py":147:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":65:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/training.py":590:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":65:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/base_layer.py":1149:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":96:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/sequential.py":398:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/functional.py":515:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/functional.py":672:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/layers/rnn/base_rnn.py":556:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":65:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/base_layer.py":1149:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":96:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/layers/rnn/simple_rnn.py":411:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/layers/rnn/base_rnn.py":722:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/backend.py":4988:1 at "/usr/local/lib/python3.9/site-packages/keras/src/backend.py":4989:1)))))))))))))))))))))))))))))))))))] at fused["StatefulPartitionedCall:", callsite("StatefulPartitionedCall@__inference_signature_wrapper_1132"("/app/quantizer/cli.py":53:1) at callsite("/app/quantizer/quantize.py":63:1 at callsite("/app/quantizer/quantize.py":114:1 at callsite("/app/quantizer/helpers.py":47:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1139:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1093:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1601:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1579:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/convert_phase.py":205:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1502:1 at "/usr/local/lib/python3.9/site-packages/tensorflow/python/saved_model/signature_serialization.py":168:1))))))))))]) at fused["StatefulPartitionedCall:", "StatefulPartitionedCall"])): error: 'tf.TensorListReserve' op requires element_shape to be static during TF Lite transformation pass
loc(callsite(callsite(fused["TensorListReserve:", callsite("sequential/simple_rnn/TensorArrayV2_1@__inference__wrapped_model_444"("/app/quantizer/cli.py":53:1) at callsite("/app/quantizer/quantize.py":63:1 at callsite("/app/quantizer/quantize.py":114:1 at callsite("/app/quantizer/helpers.py":47:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1139:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1093:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1601:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1579:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/convert_phase.py":205:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1502:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/functional.py":460:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/training.py":4031:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/base_layer.py":3470:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/base_serialization.py":61:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/layer_serialization.py":79:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/layer_serialization.py":106:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/model_serialization.py":53:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saved_model/save_impl.py":234:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saving_utils.py":158:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/saving/legacy/saving_utils.py":147:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":65:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/training.py":590:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":65:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/base_layer.py":1149:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":96:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/sequential.py":398:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/functional.py":515:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/functional.py":672:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/layers/rnn/base_rnn.py":556:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":65:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/engine/base_layer.py":1149:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py":96:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/layers/rnn/simple_rnn.py":411:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/layers/rnn/base_rnn.py":722:1 at callsite("/usr/local/lib/python3.9/site-packages/keras/src/backend.py":4988:1 at "/usr/local/lib/python3.9/site-packages/keras/src/backend.py":4989:1)))))))))))))))))))))))))))))))))))] at fused["StatefulPartitionedCall:", callsite("StatefulPartitionedCall@__inference_signature_wrapper_1132"("/app/quantizer/cli.py":53:1) at callsite("/app/quantizer/quantize.py":63:1 at callsite("/app/quantizer/quantize.py":114:1 at callsite("/app/quantizer/helpers.py":47:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1139:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1093:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1601:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1579:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/convert_phase.py":205:1 at callsite("/usr/local/lib/python3.9/site-packages/tensorflow/lite/python/lite.py":1502:1 at "/usr/local/lib/python3.9/site-packages/tensorflow/python/saved_model/signature_serialization.py":168:1))))))))))]) at fused["StatefulPartitionedCall:", "StatefulPartitionedCall"])): error: failed to legalize operation 'tf.TensorListReserve' that was explicitly marked illegal
error: Lowering tensor list ops is failed. Please consider using Select TF ops and disabling `_experimental_lower_tensor_list_ops` flag in the TFLite converter object. For example, converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS]\n converter._experimental_lower_tensor_list_ops = False
Additionally, with the `.tflite` file, I'm unable to either quantize or optimize it.
Just for information, I selected STM32 MCUs in the beginning.