i m very new to this but I am trying to solve the issue somehow. this is my convert.py file
import numpy as n
import tensorflow as tf
import coremltools as ct
print(n.__version__)
print(tf.__version__)
print(ct.__version__)
loaded_model = tf.saved_model.load("mobilenet_v2_130_224.h5")
mlmodel = ct.convert(loaded_model, inputs=[ct.ImageType()], classifier_config=ct.ClassifierConfig("labels.txt"), source='tensorflow')
mlmodel.short_description = "My Classifier"
mlmodel.license = "Apache 2.0"
spec = mlmodel.get_spec()
ct.utils.rename_feature(spec, "input_1", "imageInput")
ct.utils.rename_feature(spec, "Identity", "classResult")
mlmodel = ct.models.MLModel(spec)
print(mlmodel)
mlmodel.save("model_299x299.mlmodel")
I downloaded the model from [here][1] and unzipped on desktop. I have M1 iMac. why do I get these errors below? how can I convert this particular model into mlmodel? if my convert file is wrongly written what should be the best practice of it ?
Traceback (most recent call last):
File "/Users/asduskun/Desktop/convert.py", line 20, in <module>
mlmodel = ct.convert(loaded_model, inputs=[ct.ImageType()], classifier_config=ct.ClassifierConfig("labels.txt"), source='tensorflow')
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/_converters_entry.py", line 444, in convert
mlmodel = mil_convert(
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/mil/converter.py", line 187, in mil_convert
return _mil_convert(model, convert_from, convert_to, ConverterRegistry, MLModel, compute_units, **kwargs)
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/mil/converter.py", line 211, in _mil_convert
proto, mil_program = mil_convert_to_proto(
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/mil/converter.py", line 281, in mil_convert_to_proto
prog = frontend_converter(model, **kwargs)
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/mil/converter.py", line 99, in __call__
return tf2_loader.load()
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/mil/frontend/tensorflow/load.py", line 61, in load
self._graph_def = self._graph_def_from_model(output_names)
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/mil/frontend/tensorflow2/load.py", line 133, in _graph_def_from_model
cfs, graph_def = self._get_concrete_functions_and_graph_def()
File "/Users/asduskun/miniconda3/lib/python3.10/site-packages/coremltools/converters/mil/frontend/tensorflow2/load.py", line 125, in _get_concrete_functions_and_graph_def
raise NotImplementedError(msg.format(self.model))
NotImplementedError: Expected model format: [SavedModel | [concrete_function] | tf.keras.Model | .h5 | GraphDef], got <tensorflow.python.saved_model.load.Loader._recreate_base_user_object.<locals>._UserObject object at 0x1676455a0>
[1]: https://tfhub.dev/google/imagenet/mobilenet_v2_130_224/classification/5
Related
I have some difficulty with tensorflow_datasets when I was trying to load mnist.
python:3.7
tensorflow : 2.1.0
tensorflow_datasets has been upgraded to latest version 4.6, because the default version of tensorflow_datasets from tensorflow installation has no attribute 'load'
But now the problem is data can not be downloaded and extracted successfully.
with the following command:
datasets = tfds.load(name="mnist")
the error message is :
Downloading and preparing dataset Unknown size (download: Unknown size, generated: Unknown size, total: Unknown size) to ~\tensorflow_datasets\mnist\3.0.1...
Extraction completed...: 0 file [00:00, ? file/s]██████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 138.37 url/s]
Dl Size...: 100%|██████████████████████████████████████████████████████████████████████████| 11594722/11594722 [00:00<00:00, 373172106.07 MiB/s]
Dl Completed...: 100%|█████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 122.03 url/s]
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_datasets\core\load.py", line 327, in load
dbuilder.download_and_prepare(**download_and_prepare_kwargs)
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_datasets\core\dataset_builder.py", line 483, in download_and_prepare
download_config=download_config,
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_datasets\core\dataset_builder.py", line 1222, in _download_and_prepare
disable_shuffling=self.info.disable_shuffling,
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_datasets\core\split_builder.py", line 310, in submit_split_generation
return self._build_from_generator(**build_kwargs)
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_datasets\core\split_builder.py", line 376, in _build_from_generator
leave=False,
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tqdm\std.py", line 1195, in iter
for obj in iterable:
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_datasets\image_classification\mnist.py", line 151, in _generate_examples
images = _extract_mnist_images(data_path, num_examples)
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_datasets\image_classification\mnist.py", line 350, in _extract_mnist_images
f.read(16) # header
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_core\python\lib\io\file_io.py", line 122, in read
self._preread_check()
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_core\python\lib\io\file_io.py", line 84, in _preread_check
compat.as_bytes(self.__name), 1024 * 512)
File "C:\Users\Wilso\Anaconda3\envs\tfgpu\lib\site-packages\tensorflow_core\python\util\compat.py", line 87, in as_bytes
(bytes_or_text,))
TypeError: Expected binary or unicode string, got WindowsGPath('C:\Users\Wilso\tensorflow_datasets\downloads\extracted\GZIP.cvdf-datasets_mnist_train-images-idx3-ubyteRA_Kv3PMVG-iFHXoHqNwJlYF9WviEKQCTSyo8gNSNgk.gz')
Try:
(ds_train, ds_test), ds_info = tfds.load(
"mnist",
split=["train", "test"],
shuffle_files=True,
as_supervised=True, # will return tuple (img, label) otherwise dict
with_info=True, # able to get info about dataset
)
I covert onnxmodel to pb, and get this problem:
Traceback (most recent call last):
File "/home/fffan/fffan_files/Experiment/Example/onnx2pb/onnx2pb.py", line 45, in <module>
onnx2pb_2(onnx_input_path)
File "/home/fffan/fffan_files/Experiment/Example/onnx2pb/onnx2pb.py", line 14, in onnx2pb_2
tf_rep = prepare(model,strict=False)
File "/home/fffan/下载/onnx-tensorflow-tf-1.x/onnx_tf/backend.py", line 65, in prepare
return cls.onnx_model_to_tensorflow_rep(model, strict)
File "/home/fffan/下载/onnx-tensorflow-tf-1.x/onnx_tf/backend.py", line 85, in onnx_model_to_tensorflow_rep
return cls._onnx_graph_to_tensorflow_rep(model.graph, opset_import, strict)
File "/home/fffan/下载/onnx-tensorflow-tf-1.x/onnx_tf/backend.py", line 146, in _onnx_graph_to_tensorflow_rep
strict=strict)
File "/home/fffan/下载/onnx-tensorflow-tf-1.x/onnx_tf/backend.py", line 241, in _onnx_node_to_tensorflow_op
return handler.handle(node, tensor_dict=tensor_dict, strict=strict)
File "/home/fffan/下载/onnx-tensorflow-tf-1.x/onnx_tf/handlers/handler.py", line 60, in handle
cls.args_check(node, **kwargs)
File "/home/fffan/下载/onnx-tensorflow-tf-1.x/onnx_tf/handlers/backend/resize.py", line 89, in args_check
"Tensorflow")
File "/home/fffan/下载/onnx-tensorflow-tf-1.x/onnx_tf/common/exception.py", line 50, in __call__
raise self._func(self.get_message(op, framework))
RuntimeError: Resize coordinate_transformation_mode=pytorch_half_pixel is not supported in Tensorflow.
The code is :
import onnx
from onnx_tf.backend import prepare
import numpy as np
model = onnx.load(onnx_input_path)
tf_rep = prepare(model,strict=False)
How can I solve this problem?
ps: The algorithm model I covert is PSEnet.
I'm trying to read from a CSV file using the pandas library in python (using spyder (Python 3.7)), But I am getting an error
Traceback (most recent call last):
File "<ipython-input-104-744f03c12bee>", line 1, in
datasets = pd.read_csv('Data.csv')
File
"\Continuum\anaconda3\lib\site-packages\pandas\io\parsers.py",
line 702, in parser_f
return _read(filepath_or_buffer, kwds)
File
"\Continuum\anaconda3\lib\site-packages\pandas\io\parsers.py",
line 435, in _read
data = parser.read(nrows)
File
"\Continuum\anaconda3\lib\site-packages\pandas\io\parsers.py",
line 1154, in read
df = DataFrame(col_dict, columns=columns, index=index)
File
"\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py",
line 392, in init
mgr = init_dict(data, index, columns, dtype=dtype)
File
"\Continuum\anaconda3\lib\site-packages\pandas\core\internals\construction.py",
line 212, in init_dict
return arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
File
"\Continuum\anaconda3\lib\site-packages\pandas\core\internals\construction.py",
line 56, in arrays_to_mgr
arrays = _homogenize(arrays, index, dtype)
File
"\Continuum\anaconda3\lib\site-packages\pandas\core\internals\construction.py",
line 277, in _homogenize
raise_cast_failure=False)
File
"\Continuum\anaconda3\lib\site-packages\pandas\core\internals\construction.py",
line 582, in sanitize_array
subarr = _try_cast(data, True, dtype, copy, raise_cast_failure)
File
"\Continuum\anaconda3\lib\site-packages\pandas\core\internals\construction.py",
line 720, in _try_cast
subarr = np.array(arr, dtype=object, copy=copy)
TypeError: 'numpy.ndarray' object is not callable
I have imported the numpy library as np, as well as the pandas library as pd; the working directory has been set correctly to the same as the file save location.
import pandas as pd
datasets = pd.read_csv('Data.csv')
Following is the data that I am currently working on:
Data
Actually your file(data.csv) is not a csv file. Its in PNG format. So, you can use PIL module in python.
from PIL import Image
imframe = Image.open('data.csv')
imframe
I have been following the sentdex tutorial on a tensorflow chatbot, and on coming t train the chatbot using nmt, tensorflow repeatedly spits out -
tensorflow.python.framework.errors_impl.NotFoundError: /home/paperspace/nmt-chatbot/data/tst2012.from; No such file or directory
I have tried uninstalling and reinstalling tensorflow, but nothing is working
The following is all the error messages I receive:
Traceback (most recent call last):
File "train.py", line 18, in <module>
tf.app.run(main=nmt.main, argv=[os.getcwd() + '\nmt\nmt\nmt.py'] + unparsed)
File "/home/paperspace/.local/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "/home/paperspace/nmt-chatbot/nmt/nmt/nmt.py", line 539, in main
run_main(FLAGS, default_hparams, train_fn, inference_fn)
File "/home/paperspace/nmt-chatbot/nmt/nmt/nmt.py", line 532, in run_main
train_fn(hparams, target_session=target_session)
File "/home/paperspace/nmt-chatbot/nmt/nmt/train.py", line 229, in train
sample_src_data = inference.load_data(dev_src_file)
File "/home/paperspace/nmt-chatbot/nmt/nmt/inference.py", line 75, in load_data
inference_data = f.read().splitlines()
File "/usr/lib/python3.6/codecs.py", line 495, in read
newdata = self.stream.read()
File "/home/paperspace/.local/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 119, in read
self._preread_check()
File "/home/paperspace/.local/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 79, in _preread_check
compat.as_bytes(self.__name), 1024 * 512, status)
File "/home/paperspace/.local/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 473, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.NotFoundError: /home/paperspace/nmt-chatbot/data/tst2012.from; No such file or directory
The code in the train.py file is...
import sys
import os
import argparse
from setup.settings import hparams
sys.path.append(os.path.realpath(os.path.dirname(__file__)))
sys.path.append(os.path.realpath(os.path.dirname(__file__)) + "/nmt")
from nmt import nmt
import tensorflow as tf
# Modified autorun from nmt.py (bottom of the file)
# We want to use original argument parser (for validation, etc)
nmt_parser = argparse.ArgumentParser()
nmt.add_arguments(nmt_parser)
# But we have to hack settings from our config in there instead of commandline options
nmt.FLAGS, unparsed = nmt_parser.parse_known_args(['--'+k+'='+str(v) for k,v in hparams.items()])
# And now we can run TF with modified arguments
tf.app.run(main=nmt.main, argv=[os.getcwd() + '\nmt\nmt\nmt.py'] + unparsed)
Any help would be really appreciated
I am trying a simple parallel computation in Dask.
This is my code.
import time
import dask as dask
import dask.distributed as distributed
import dask.dataframe as dd
import dask.delayed as delayed
from dask.distributed import Client,progress
client = Client('localhost:8786')
df = dd.read_csv('file.csv')
ddf = df.groupby(['col1'])[['col2']].sum()
ddf = ddf.compute()
print ddf
It seems fine from the documentation but on running I am getting this :
Traceback (most recent call last):
File "dask_prg1.py", line 17, in <module>
ddf = ddf.compute()
File "/usr/local/lib/python2.7/site-packages/dask/base.py", line 156, in compute
(result,) = compute(self, traverse=False, **kwargs)
File "/usr/local/lib/python2.7/site-packages/dask/base.py", line 402, in compute
results = schedule(dsk, keys, **kwargs)
File "/usr/local/lib/python2.7/site-packages/distributed/client.py", line 2159, in get
direct=direct)
File "/usr/local/lib/python2.7/site-packages/distributed/client.py", line 1562, in gather
asynchronous=asynchronous)
File "/usr/local/lib/python2.7/site-packages/distributed/client.py", line 652, in sync
return sync(self.loop, func, *args, **kwargs)
File "/usr/local/lib/python2.7/site-packages/distributed/utils.py", line 275, in sync
six.reraise(*error[0])
File "/usr/local/lib/python2.7/site-packages/distributed/utils.py", line 260, in f
result[0] = yield make_coro()
File "/usr/local/lib/python2.7/site-packages/tornado/gen.py", line 1099, in run
value = future.result()
File "/usr/local/lib/python2.7/site-packages/tornado/concurrent.py", line 260, in result
raise_exc_info(self._exc_info)
File "/usr/local/lib/python2.7/site-packages/tornado/gen.py", line 1107, in run
yielded = self.gen.throw(*exc_info)
File "/usr/local/lib/python2.7/site-packages/distributed/client.py", line 1439, in _gather
traceback)
File "/usr/local/lib/python2.7/site-packages/dask/bytes/core.py", line 122, in read_block_from_file
with lazy_file as f:
File "/usr/local/lib/python2.7/site-packages/dask/bytes/core.py", line 166, in __enter__
f = SeekableFile(self.fs.open(self.path, mode=mode))
File "/usr/local/lib/python2.7/site-packages/dask/bytes/local.py", line 58, in open
return open(self._normalize_path(path), mode=mode)
IOError: [Errno 2] No such file or directory: 'file.csv'
I am not understanding what is wrong.Kindly help me with this .Thank you in advance .
You may wish to pass the absolute file path to read_csv. The reason is, that you are giving the work of opening and reading the file to a dask worker, and you might not have started that worked with the same working directory as your script/session.