8
आवंटित करने की कोशिश कर स्मृति से बाहर निकलें मैं टेंसर फ्लो संस्करण 0.7.1, 64-बिट GPU- सक्षम, पाइप के साथ स्थापित, और उबंटू 14.04 के साथ एक पीसी पर चला रहा हूं। मेरी समस्या यह है कि मेरे नेटवर्क का निर्माण करते समय टेंसर फ्लो मेमोरी से बाहर हो रहा है, भले ही मेरी गणना के आधार पर, मेरे जीपीयू पर पर्याप्त जगह होनी चाहिए।टेंसर फ्लो:
नीचे मेरे कोड का एक न्यूनतम उदाहरण है, जो टेंसर फ्लो एमएनआईएसटी ट्यूटोरियल पर आधारित है। नेटवर्क एक दो परत पूरी तरह से जुड़े नेटवर्क है, और छिपे हुए परत में नोड्स की संख्या चर n द्वारा परिभाषित की गई है। प्रशिक्षण minibatch के आकार 1. है यहाँ मेरी कोड है:
n = 23000
mnist = read_data_sets('MINST_Data', one_hot=True)
session = tf.InteractiveSession()
x = tf.placeholder(tf.float32, [None, 784])
W1 = tf.Variable(tf.truncated_normal([784, n], stddev=0.1))
b1 = tf.Variable(tf.constant(0.1, shape=[n]))
nn1 = tf.matmul(x, W1) + b1
W2 = tf.Variable(tf.truncated_normal([n, 10], stddev=0.1))
b2 = tf.Variable(tf.constant(0.1, shape=[10]))
nn2 = tf.matmul(nn1, W2) + b2
y = tf.nn.softmax(nn2)
y_ = tf.placeholder(tf.float32, [None, 10])
cross_entropy = -tf.reduce_sum(y_*tf.log(y))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
init = tf.initialize_all_variables()
sess = tf.Session()
sess.run(init)
for i in range(1000):
batch_xs, batch_ys = mnist.train.next_batch(1)
sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
अब, अगर n <= 22000, तो नेटवर्क ठीक चलाता है।
W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:211] Ran out of memory trying to allocate 877.38MiB. See logs for memory state
W tensorflow/core/kernels/cwise_ops_common.cc:56] Resource exhausted: OOM when allocating tensor with shape[10000,23000]
लेकिन, मेरा गणना के अनुसार, वहाँ नहीं स्मृति के साथ एक समस्या नहीं होनी चाहिए: हालांकि, अगर n >= 23000, मैं निम्नलिखित त्रुटि मिलती है। नेटवर्क में मानकों की संख्या इस प्रकार है:
First layer weights: 784 * n
First layer biases: n
Second layer weights: 10 * n
Second layer biases: 10
Total: 795n + 10
तो n = 23000 के साथ, और float32 डेटा का उपयोग कर, कुल स्मृति नेटवर्क के लिए आवश्यक इसलिए 73.1 एमबी होना चाहिए।
अब, मेरा ग्राफिक्स कार्ड एनवीआईडीआईए जेफफोर्स जीटीएक्स 780 टीआई है, जिसमें 3072 एमबी मेमोरी है। मेरी ग्राफिक्स कार्ड खोजने के बाद, टेन्सर प्रवाह बाहर प्रिंट निम्नलिखित:
Total memory: 3.00GiB
Free memory: 2.32GiB
तो, वहाँ के आसपास 2.32 जीबी मेमोरी उपलब्ध है, जो 73.1 एमबी ऊपर गणना की तुलना में कहीं अधिक है होना चाहिए। मिनीबैच आकार 1 है, इसलिए इसका न्यूनतम प्रभाव है। क्यों यह त्रुटि आ रही है?
मैं भी अब अपने लैपटॉप है, जो एक NVIDA GeForce GTX 880 M GPU है पर इस कोशिश की है। यहां, टेंसर फ्लो Free memory: 7.60GiB पढ़ता है। ऊपर जैसा ही कोड चला रहा है, यह मुझे लगभग n = 700,000 पर एक स्मृति त्रुटि देता है, जो 2.2 जीबी के बराबर है। यह थोड़ा और समझ में आता है, और उस बिंदु से काफी अधिक है जिस पर मेरा पीसी कोड टूट जाता है। हालांकि, यह अभी भी मुझे परेशान कर रहा है कि यह 7.6 जीबी अंक के करीब क्यों नहीं टूटता है।
मेरे पीसी पर उपरोक्त कोड चल रहा है, n = 23000 साथ, जबकि टेन्सर प्रवाह से पूर्ण उत्पादन, है:
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:900] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0 with properties:
name: GeForce GTX 780 Ti
major: 3 minor: 5 memoryClockRate (GHz) 1.0455
pciBusID 0000:01:00.0
Total memory: 3.00GiB
Free memory: 2.32GiB
I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:717] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 780 Ti, pci bus id: 0000:01:00.0)
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 1.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 2.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 4.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 8.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 16.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 32.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 64.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 128.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 256.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 512.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 1.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 2.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 4.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 8.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 16.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 32.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 64.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 128.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 256.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 512.00MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 1.00GiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 2.00GiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 4.00GiB
I tensorflow/core/common_runtime/gpu/gpu_device.cc:717] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 780 Ti, pci bus id: 0000:01:00.0)
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:73] Allocating 2.03GiB bytes.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:83] GPU 0 memory begins at 0xb04720000 extends to 0xb86295000
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (256): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (1024): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (2048): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (4096): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (8192): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (16384): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (32768): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (65536): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (131072): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (262144): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (524288): Total Chunks: 2, Chunks in use: 0 819.0KiB allocated for chunks. 390.6KiB client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (1048576): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (2097152): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (4194304): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (8388608): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (16777216): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (33554432): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (67108864): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (134217728): Total Chunks: 1, Chunks in use: 0 68.79MiB allocated for chunks. 29.91MiB client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (268435456): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (536870912): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (1073741824): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (2147483648): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:431] Bin (4294967296): Total Chunks: 0, Chunks in use: 0 0B allocated for chunks. 0B client-requested for chunks. 0B in use in bin. 0B client-requested in use in bin.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:450] Bin for 877.38MiB was 1.00GiB, Chunk State:
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d239400 of size 80128
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d1d7600 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d24cd00 of size 438528
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d1d7500 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb1a3e3200 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb1a302800 of size 920064
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb15d58800 of size 920064
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb08cf7500 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb04736b00 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d2b7f00 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb15e39200 of size 72128000
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb08c16b00 of size 920064
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb15c61500 of size 92160
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb04736d00 of size 72128000
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d2b8100 of size 72128000
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb15c4ad00 of size 92160
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb04736a00 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d2b7e00 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d1d7900 of size 400128
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb04720200 of size 92160
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb04736c00 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb08cf7600 of size 72128000
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb1a3e3300 of size 1810570496
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d1c0c00 of size 92160
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb08c00300 of size 92160
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d2b8000 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d1d7800 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb04720100 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d1d7700 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb04720000 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb0d1d7400 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb11781700 of size 72128000
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb15c77d00 of size 256
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:465] Chunk at 0xb15c77e00 of size 920064
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:468] Summary of in-use Chunks by size:
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 16 Chunks of size 256 totalling 4.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 1 Chunks of size 80128 totalling 78.2KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 5 Chunks of size 92160 totalling 450.0KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 1 Chunks of size 400128 totalling 390.8KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 1 Chunks of size 438528 totalling 428.2KiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 4 Chunks of size 920064 totalling 3.51MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 5 Chunks of size 72128000 totalling 343.93MiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:471] 1 Chunks of size 1810570496 totalling 1.69GiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:475] Sum Total of in-use chunks: 2.03GiB
W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:211] Ran out of memory trying to allocate 877.38MiB. See logs for memory state
W tensorflow/core/kernels/cwise_ops_common.cc:56] Resource exhausted: OOM when allocating tensor with shape[10000,23000]
W tensorflow/core/common_runtime/executor.cc:1102] 0x50f40e0 Compute status: Resource exhausted: OOM when allocating tensor with shape[10000,23000]
[[Node: add = Add[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](MatMul, Variable_1/read)]]
W tensorflow/core/common_runtime/executor.cc:1102] 0x3234d30 Compute status: Resource exhausted: OOM when allocating tensor with shape[10000,23000]
[[Node: add = Add[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](MatMul, Variable_1/read)]]
[[Node: range_1/_13 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_97_range_1", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
W tensorflow/core/common_runtime/executor.cc:1102] 0x3234d30 Compute status: Resource exhausted: OOM when allocating tensor with shape[10000,23000]
[[Node: add = Add[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](MatMul, Variable_1/read)]]
[[Node: Cast/_11 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_96_Cast", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Traceback (most recent call last):
File "/home/jrowlay/Projects/Tensor_Flow_Tutorial/MNIST_CNN_Simple/memory_test.py", line 232, in <module>
print(sess.run(accuracy, feed_dict={x: mnist.test.images, y_: mnist.test.labels}))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 315, in run
return self._run(None, fetches, feed_dict)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 511, in _run
feed_dict_string)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 564, in _do_run
target_list)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 586, in _do_call
e.code)
tensorflow.python.framework.errors.ResourceExhaustedError: OOM when allocating tensor with shape[10000,23000]
[[Node: add = Add[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](MatMul, Variable_1/read)]]
[[Node: range_1/_13 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_97_range_1", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op u'add', defined at:
File "/home/jrowlay/Projects/Tensor_Flow_Tutorial/MNIST_CNN_Simple/memory_test.py", line 215, in <module>
nn1 = tf.matmul(x, W1) + b1
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/math_ops.py", line 468, in binary_op_wrapper
return func(x, y, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_math_ops.py", line 44, in add
return _op_def_lib.apply_op("Add", x=x, y=y, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/op_def_library.py", line 655, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2040, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1087, in __init__
self._traceback = _extract_stack()
बस अनुमान लगाया जा सकता है लेकिन क्या यह हो सकता है कि डेटासेट किसी भी तरह GPU में स्मृति में है? डेटासेट से कुछ डेटा निकालने का प्रयास करें और फिर मेमोरी की जांच करें। यह डेटासेट नहीं होना चाहिए लेकिन ... कौन जानता है। – jorgemf