Sorry for my lack of knowledge, but I am trying to run the example on Tensorflow:
import numpy as np
import tensorflow as tf
feature_columns = [tf.feature_column.numeric_column("x", shape=[1])]
estimator = tf.estimator.LinearRegressor(feature_columns=feature_columns)
x_train = np.array([1., 2., 3., 4.])
y_train = np.array([0., -1., -2., -3.])
x_eval = np.array([2., 5., 8., 1.])
y_eval = np.array([-1.01, -4.1, -7, 0.])
input_fn = tf.estimator.inputs.numpy_input_fn(
{"x": x_train}, y_train, batch_size=4, num_epochs=None, shuffle=True)
train_input_fn = tf.estimator.inputs.numpy_input_fn(
{"x": x_train}, y_train, batch_size=4, num_epochs=1000, shuffle=False)
eval_input_fn = tf.estimator.inputs.numpy_input_fn(
{"x": x_eval}, y_eval, batch_size=4, num_epochs=1000, shuffle=False)
estimator.train(input_fn=input_fn, steps=1000)
train_metrics = estimator.evaluate(input_fn=train_input_fn)
eval_metrics = estimator.evaluate(input_fn=eval_input_fn)
print("train metrics: %r"% train_metrics)
print("eval metrics: %r"% eval_metrics)
I got the following error message: PermissionDeniedError: Failed to delete a file: C:\Users\Jeff\AppData\Local\Temp\tmpgpmjek44\graph.pbtxt.tmpe31b9f4677cb426fbaef32dadeaf1a4d; Permission denied
I found the error comes from the line "estimator.train(input_fn=input_fn, steps=1000)". I tried to look at the folder and the file. They are granted full control already. This maybe a stupid question but what can possibly the cause and solution here. Thank you so much in advance!
UPDATE:
I ran it from the root and got the following:
(C:\Users\Jeff\Anaconda3) C:\Users\Jeff>python test.py WARNING:tensorflow:Using temporary folder as model directory: C:\Users\Jeff\AppData\Local\Temp\tmp0yywjv30 2017-11-10 22:54:59.808636: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2 2017-11-10 22:55:00.096842: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1030] Found device 0 with properties: name: GeForce GTX 1060 major: 6 minor: 1 memoryClockRate(GHz): 1.6705 pciBusID: 0000:01:00.0 totalMemory: 6.00GiB freeMemory: 4.99GiB 2017-11-10 22:55:00.096927: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1060, pci bus id: 0000:01:00.0, compute capability: 6.1) 2017-11-10 22:55:02.512317: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\stream_executor\cuda\cuda_blas.cc:366] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED 2017-11-10 22:55:02.513461: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\stream_executor\cuda\cuda_blas.cc:366] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED 2017-11-10 22:55:02.513601: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\stream_executor\cuda\cuda_blas.cc:366] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED 2017-11-10 22:55:02.514975: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\stream_executor\cuda\cuda_blas.cc:366] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED 2017-11-10 22:55:02.515067: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\stream_executor\stream.cc:1901] attempting to perform BLAS operation using StreamExecutor without BLAS support Traceback (most recent call last): File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1323, in _do_call return fn(*args) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1302, in _run_fn status, run_metadata) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 473, in exit c_api.TF_GetCode(self.status.status)) tensorflow.python.framework.errors_impl.InternalError: Blas GEMV launch failed: m=1, n=4 [[Node: linear/linear_model/x/weighted_sum = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](linear/linear_model/x/Reshape, linear/linear_model/x/weights)]] [[Node: linear/gradients/linear/linear_model/x/weighted_sum_grad/tuple/control_dependency_1/_85 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_184_linear/gradients/linear/linear_model/x/weighted_sum_grad/tuple/control_dependency_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "test.py", line 39, in estimator.train(input_fn=input_fn, steps=1000) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\estimator.py", line 302, in train loss = self._train_model(input_fn, hooks, saving_listeners) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\estimator.py", line 783, in _train_model _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss]) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\training\monitored_session.py", line 521, in run run_metadata=run_metadata) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\training\monitored_session.py", line 892, in run run_metadata=run_metadata) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\training\monitored_session.py", line 967, in run raise six.reraise(*original_exc_info) File "C:\Users\Jeff\Anaconda3\lib\site-packages\six.py", line 693, in reraise raise value File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\training\monitored_session.py", line 952, in run return self._sess.run(*args, **kwargs) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1024, in run run_metadata=run_metadata) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\training\monitored_session.py", line 827, in run return self._sess.run(*args, **kwargs) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 889, in run run_metadata_ptr) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1120, in _run feed_dict_tensor, options, run_metadata) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1317, in _do_run options, run_metadata) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1336, in _do_call raise type(e)(node_def, op, message) tensorflow.python.framework.errors_impl.InternalError: Blas GEMV launch failed: m=1, n=4 [[Node: linear/linear_model/x/weighted_sum = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](linear/linear_model/x/Reshape, linear/linear_model/x/weights)]] [[Node: linear/gradients/linear/linear_model/x/weighted_sum_grad/tuple/control_dependency_1/_85 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_184_linear/gradients/linear/linear_model/x/weighted_sum_grad/tuple/control_dependency_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
Caused by op 'linear/linear_model/x/weighted_sum', defined at: File "test.py", line 39, in estimator.train(input_fn=input_fn, steps=1000) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\estimator.py", line 302, in train loss = self._train_model(input_fn, hooks, saving_listeners) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\estimator.py", line 711, in _train_model features, labels, model_fn_lib.ModeKeys.TRAIN, self.config) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\estimator.py", line 694, in _call_model_fn model_fn_results = self._model_fn(features=features, **kwargs) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\canned\linear.py", line 348, in _model_fn config=config) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\canned\linear.py", line 118, in _linear_model_fn logits = logit_fn(features=features) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\estimator\canned\linear.py", line 70, in linear_logit_fn features=features, feature_columns=feature_columns, units=units) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\feature_column\feature_column.py", line 321, in linear_model column, builder, units, weight_collections, trainable)) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\feature_column\feature_column.py", line 1376, in _create_dense_column_weighted_sum return math_ops.matmul(tensor, weight, name='weighted_sum') File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1891, in matmul a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 2436, in _mat_mul name=name) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper op_def=op_def) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2956, in create_op op_def=op_def) File "C:\Users\Jeff\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1470, in init self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InternalError (see above for traceback): Blas GEMV launch failed: m=1, n=4 [[Node: linear/linear_model/x/weighted_sum = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](linear/linear_model/x/Reshape, linear/linear_model/x/weights)]] [[Node: linear/gradients/linear/linear_model/x/weighted_sum_grad/tuple/control_dependency_1/_85 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_184_linear/gradients/linear/linear_model/x/weighted_sum_grad/tuple/control_dependency_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
