Any alternative operators equivalent to Iterators available for TFLITE?I am trying to do a quantized mobilenet model to tensorflow lite model, but run into an errortensorflow tools: graph_transform v/s tocoConvert (Fused)BatchNorm to convolution / add for running MobileNet on TensorflowLiteHow to train mobilenet-v1 quantized model to use on TF Litetensorflow lite conversion for LSTM ModelError converting .Pb filte to tflite using toco(tensorflow)add an op in tensorflow, but type is errorWhy do I convert.h5 files to.tflite files sometimes, but not when I change the dimensions of trainingTensorflow TF-Lite toco converter, oneshot iterator op missingTensorflow Lite toco --mean_values --std_values?
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Any alternative operators equivalent to Iterators available for TFLITE?
I am trying to do a quantized mobilenet model to tensorflow lite model, but run into an errortensorflow tools: graph_transform v/s tocoConvert (Fused)BatchNorm to convolution / add for running MobileNet on TensorflowLiteHow to train mobilenet-v1 quantized model to use on TF Litetensorflow lite conversion for LSTM ModelError converting .Pb filte to tflite using toco(tensorflow)add an op in tensorflow, but type is errorWhy do I convert.h5 files to.tflite files sometimes, but not when I change the dimensions of trainingTensorflow TF-Lite toco converter, oneshot iterator op missingTensorflow Lite toco --mean_values --std_values?
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
I already requested few operators to be supported for TFLITE. But was wondering is there an alternative to iterate the dataset without using iterators?
Goal is to iterate all training data by batches using MNIST training dataset (55K images)
Here's a snippet:
train_data = tf.data.Dataset.from_tensor_slices(train)
train_data = train_data.shuffle(10000)
train_data = train_data.batch(batch_size)
iterator = tf.data.Iterator.from_structure(train_data.output_types,
train_data.output_shapes)
img, label = iterator.get_next()
train_init = iterator.make_initializer(train_data)
Errors in TFLITE conversion:
tensorflow.lite.python.convert.ConverterError: TOCO failed. See console for info.
2019-03-27 17:40:24.648521: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorV2
2019-03-27 17:40:24.656267: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 20
2019-03-27 17:40:24.656283: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorGetNext
2019-03-27 17:40:24.656301: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656376: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656460: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: SoftmaxCrossEntropyWithLogits
2019-03-27 17:40:24.656709: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.656884: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.657083: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 1: 13 operators, 24 arrays (0 quantized)
2019-03-27 17:40:24.657094: F tensorflow/lite/toco/tooling_util.cc:897] Check failed: GetOpWithInput(model, input_array.name()) Specified input array "weights" is not consumed by any op in this graph. Is it a typo? To silence this message, pass this flag: allow_nonexistent_arrays
tensorflow tensorflow-lite
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
add a comment |
I already requested few operators to be supported for TFLITE. But was wondering is there an alternative to iterate the dataset without using iterators?
Goal is to iterate all training data by batches using MNIST training dataset (55K images)
Here's a snippet:
train_data = tf.data.Dataset.from_tensor_slices(train)
train_data = train_data.shuffle(10000)
train_data = train_data.batch(batch_size)
iterator = tf.data.Iterator.from_structure(train_data.output_types,
train_data.output_shapes)
img, label = iterator.get_next()
train_init = iterator.make_initializer(train_data)
Errors in TFLITE conversion:
tensorflow.lite.python.convert.ConverterError: TOCO failed. See console for info.
2019-03-27 17:40:24.648521: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorV2
2019-03-27 17:40:24.656267: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 20
2019-03-27 17:40:24.656283: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorGetNext
2019-03-27 17:40:24.656301: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656376: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656460: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: SoftmaxCrossEntropyWithLogits
2019-03-27 17:40:24.656709: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.656884: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.657083: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 1: 13 operators, 24 arrays (0 quantized)
2019-03-27 17:40:24.657094: F tensorflow/lite/toco/tooling_util.cc:897] Check failed: GetOpWithInput(model, input_array.name()) Specified input array "weights" is not consumed by any op in this graph. Is it a typo? To silence this message, pass this flag: allow_nonexistent_arrays
tensorflow tensorflow-lite
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
add a comment |
I already requested few operators to be supported for TFLITE. But was wondering is there an alternative to iterate the dataset without using iterators?
Goal is to iterate all training data by batches using MNIST training dataset (55K images)
Here's a snippet:
train_data = tf.data.Dataset.from_tensor_slices(train)
train_data = train_data.shuffle(10000)
train_data = train_data.batch(batch_size)
iterator = tf.data.Iterator.from_structure(train_data.output_types,
train_data.output_shapes)
img, label = iterator.get_next()
train_init = iterator.make_initializer(train_data)
Errors in TFLITE conversion:
tensorflow.lite.python.convert.ConverterError: TOCO failed. See console for info.
2019-03-27 17:40:24.648521: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorV2
2019-03-27 17:40:24.656267: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 20
2019-03-27 17:40:24.656283: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorGetNext
2019-03-27 17:40:24.656301: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656376: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656460: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: SoftmaxCrossEntropyWithLogits
2019-03-27 17:40:24.656709: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.656884: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.657083: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 1: 13 operators, 24 arrays (0 quantized)
2019-03-27 17:40:24.657094: F tensorflow/lite/toco/tooling_util.cc:897] Check failed: GetOpWithInput(model, input_array.name()) Specified input array "weights" is not consumed by any op in this graph. Is it a typo? To silence this message, pass this flag: allow_nonexistent_arrays
tensorflow tensorflow-lite
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
I already requested few operators to be supported for TFLITE. But was wondering is there an alternative to iterate the dataset without using iterators?
Goal is to iterate all training data by batches using MNIST training dataset (55K images)
Here's a snippet:
train_data = tf.data.Dataset.from_tensor_slices(train)
train_data = train_data.shuffle(10000)
train_data = train_data.batch(batch_size)
iterator = tf.data.Iterator.from_structure(train_data.output_types,
train_data.output_shapes)
img, label = iterator.get_next()
train_init = iterator.make_initializer(train_data)
Errors in TFLITE conversion:
tensorflow.lite.python.convert.ConverterError: TOCO failed. See console for info.
2019-03-27 17:40:24.648521: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorV2
2019-03-27 17:40:24.656267: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 20
2019-03-27 17:40:24.656283: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: IteratorGetNext
2019-03-27 17:40:24.656301: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656376: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 2
2019-03-27 17:40:24.656460: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: SoftmaxCrossEntropyWithLogits
2019-03-27 17:40:24.656709: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.656884: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 21 operators, 35 arrays (0 quantized)
2019-03-27 17:40:24.657083: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 1: 13 operators, 24 arrays (0 quantized)
2019-03-27 17:40:24.657094: F tensorflow/lite/toco/tooling_util.cc:897] Check failed: GetOpWithInput(model, input_array.name()) Specified input array "weights" is not consumed by any op in this graph. Is it a typo? To silence this message, pass this flag: allow_nonexistent_arrays
tensorflow tensorflow-lite
tensorflow tensorflow-lite
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
asked Mar 28 at 6:05
Joseph D.Joseph D.
5,1692 gold badges14 silver badges40 bronze badges
5,1692 gold badges14 silver badges40 bronze badges
add a comment |
add a comment |
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