Model.fit() 是否将整个训练数据集上传到 GPU？
Does Model.fit() upload the whole training dataset to the GPU?
我正在使用 keras API、tensorflow 后端在几个 GB 数据集上训练 LSTM。当 运行 Model.fit() 对一些内存数据 (numpy) 时，它会在一个请求中分配 8GB 内存，这在仅加载一小部分数据时不会发生。我的 GPU 不能同时使用模型参数和 8GB，它会耗尽内存并停止。我很确定这在我从 TF2 beta 升级到 TF2rc 后开始发生。我是这样称呼适合的：
tb = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
es = keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=patience*2, restore_best_weights=True)
lr_reduce = keras.callbacks.ReduceLROnPlateau(factor=0.1, patience=patience, verbose=1)
chkpointing = keras.callbacks.ModelCheckpoint(weight_fname, monitor='val_loss', verbose=0, save_best_only=True,
save_weights_only=True, mode='auto')
model.fit(train_data_x, train_data_y, validation_data=(test_data_x, test_data_y), batch_size=cfg['batch_size'],
epochs=nepochs, validation_freq=1, callbacks=[lr_reduce, es, tb, chkpointing],
class_weight=cfg['class_weight'], shuffle=True)
是否打算在 GPU 上为整个数据集分配 space？我怎样才能防止它发生？
编辑：
更新了代码以限制内存分配。它确实限制了它，因为它表明 TF 可以访问比以前更少的内存，但它仍然尝试分配 8.14GB。这是我限制内存和 select GPU 的方法：
def select_gpu(gpu_id=-1, max_usage=.5): # max 2 gpu only
os.environ["CUDA_VISIBLE_DEVICES"] = str(gpu_id) if gpu_id != -1 else '0,1'
gpus = tf.config.experimental.list_physical_devices('GPU')
max_memory = 11534 # MB got from: grep -i --color memory /var/log/Xorg.0.log
for gpu in gpus:
print('GPU FOUND:', gpu)
tf.config.experimental.set_memory_growth(gpu, True) # FIXME true
tf.config.experimental.set_virtual_device_configuration(gpu,
[tf.config.experimental.VirtualDeviceConfiguration(memory_limit=max_memory * max_usage)])
print('RUNNING ON GPU #{}'.format(gpu_id))
# ... just call select_gpu(0) in the beginning of the script
这是错误：
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
time_distributed (TimeDistri (None, 42, 256) 7168
_________________________________________________________________
cu_dnnlstm (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_1 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_2 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_3 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_4 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_5 (CuDNNLSTM) (None, 256) 526336
_________________________________________________________________
dense_1 (Dense) (None, 256) 65792
_________________________________________________________________
dense_2 (Dense) (None, 1) 257
=================================================================
Total params: 3,231,233
Trainable params: 3,231,233
Non-trainable params: 0
_________________________________________________________________
None
2019-10-27 12:36:48.833843: W tensorflow/core/common_runtime/bfc_allocator.cc:419] Allocator (GPU_0_bfc) ran out of memory trying to allocate 8.14GiB (rounded to 8738821888). Current allocation summary follows.
2019-10-27 12:36:48.833927: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (256): Total Chunks: 16, Chunks in use: 15. 4.0KiB allocated for chunks. 3.8KiB in use in bin. 72B client-requested in use in bin.
2019-10-27 12:36:48.833944: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (512): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.833958: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (1024): Total Chunks: 5, Chunks in use: 4. 5.5KiB allocated for chunks. 4.2KiB in use in bin. 4.0KiB client-requested in use in bin.
2019-10-27 12:36:48.833970: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (2048): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.833982: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (4096): Total Chunks: 1, Chunks in use: 0. 4.8KiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.833998: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (8192): Total Chunks: 6, Chunks in use: 6. 49.8KiB allocated for chunks. 49.8KiB in use in bin. 48.0KiB client-requested in use in bin.
2019-10-27 12:36:48.834012: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (16384): Total Chunks: 1, Chunks in use: 1. 27.0KiB allocated for chunks. 27.0KiB in use in bin. 27.0KiB client-requested in use in bin.
2019-10-27 12:36:48.834023: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (32768): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834034: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (65536): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834045: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (131072): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834060: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (262144): Total Chunks: 1, Chunks in use: 1. 504.0KiB allocated for chunks. 504.0KiB in use in bin. 256.0KiB client-requested in use in bin.
2019-10-27 12:36:48.834073: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (524288): Total Chunks: 1, Chunks in use: 0. 512.0KiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834088: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (1048576): Total Chunks: 12, Chunks in use: 12. 12.00MiB allocated for chunks. 12.00MiB in use in bin. 12.00MiB client-requested in use in bin.
2019-10-27 12:36:48.834099: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (2097152): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834110: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (4194304): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834122: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (8388608): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834132: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (16777216): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834143: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (33554432): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834156: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (67108864): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834167: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (134217728): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834180: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (268435456): Total Chunks: 1, Chunks in use: 0. 4.49GiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834193: I tensorflow/core/common_runtime/bfc_allocator.cc:885] Bin for 8.14GiB was 256.00MiB, Chunk State:
2019-10-27 12:36:48.834213: I tensorflow/core/common_runtime/bfc_allocator.cc:891] Size: 4.49GiB | Requested Size: 1.00MiB | in_use: 0 | bin_num: 20, prev: Size: 1.00MiB | Requested Size: 1.00MiB | in_use: 1 | bin_num: -1
2019-10-27 12:36:48.834223: I tensorflow/core/common_runtime/bfc_allocator.cc:898] Next region of size 4837081088
2019-10-27 12:36:48.834237: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000000 next 1 of size 256
2019-10-27 12:36:48.834247: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000100 next 2 of size 256
2019-10-27 12:36:48.834257: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000200 next 3 of size 1280
2019-10-27 12:36:48.834267: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000700 next 4 of size 256
2019-10-27 12:36:48.834277: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000800 next 5 of size 1024
2019-10-27 12:36:48.834287: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000c00 next 8 of size 256
2019-10-27 12:36:48.834296: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000d00 next 9 of size 256
2019-10-27 12:36:48.834306: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000e00 next 10 of size 256
2019-10-27 12:36:48.834316: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000f00 next 13 of size 256
2019-10-27 12:36:48.834325: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001000 next 34 of size 256
2019-10-27 12:36:48.834335: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001100 next 35 of size 256
2019-10-27 12:36:48.834344: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001200 next 37 of size 256
2019-10-27 12:36:48.834354: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001300 next 16 of size 256
2019-10-27 12:36:48.834363: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001400 next 14 of size 256
2019-10-27 12:36:48.834373: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6001500 next 40 of size 1280
2019-10-27 12:36:48.834382: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001a00 next 41 of size 1024
2019-10-27 12:36:48.834392: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6001e00 next 18 of size 4864
2019-10-27 12:36:48.834402: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6003100 next 19 of size 8192
2019-10-27 12:36:48.834411: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005100 next 36 of size 1024
2019-10-27 12:36:48.834420: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005500 next 39 of size 256
2019-10-27 12:36:48.834430: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005600 next 42 of size 256
2019-10-27 12:36:48.834439: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005700 next 43 of size 256
2019-10-27 12:36:48.834449: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6005800 next 21 of size 256
2019-10-27 12:36:48.834459: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005900 next 22 of size 8192
2019-10-27 12:36:48.834469: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6007900 next 25 of size 8192
2019-10-27 12:36:48.834478: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6009900 next 28 of size 8192
2019-10-27 12:36:48.834488: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf600b900 next 6 of size 9984
2019-10-27 12:36:48.834500: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf600e000 next 7 of size 27648
2019-10-27 12:36:48.834509: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6014c00 next 33 of size 8192
2019-10-27 12:36:48.834519: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6016c00 next 38 of size 524288
2019-10-27 12:36:48.834528: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6096c00 next 17 of size 516096
2019-10-27 12:36:48.834538: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6114c00 next 12 of size 1048576
2019-10-27 12:36:48.834548: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6214c00 next 11 of size 1048576
2019-10-27 12:36:48.834558: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6314c00 next 20 of size 1048576
2019-10-27 12:36:48.834567: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6414c00 next 15 of size 1048576
2019-10-27 12:36:48.834577: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6514c00 next 24 of size 1048576
2019-10-27 12:36:48.834586: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6614c00 next 23 of size 1048576
2019-10-27 12:36:48.834595: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6714c00 next 27 of size 1048576
2019-10-27 12:36:48.834605: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6814c00 next 26 of size 1048576
2019-10-27 12:36:48.834614: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6914c00 next 30 of size 1048576
2019-10-27 12:36:48.834623: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6a14c00 next 29 of size 1048576
2019-10-27 12:36:48.834633: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6b14c00 next 32 of size 1048576
2019-10-27 12:36:48.834642: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6c14c00 next 31 of size 1048576
2019-10-27 12:36:48.834652: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6d14c00 next 18446744073709551615 of size 4823364608
2019-10-27 12:36:48.834661: I tensorflow/core/common_runtime/bfc_allocator.cc:914] Summary of in-use Chunks by size:
2019-10-27 12:36:48.834673: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 15 Chunks of size 256 totalling 3.8KiB
2019-10-27 12:36:48.834684: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 3 Chunks of size 1024 totalling 3.0KiB
2019-10-27 12:36:48.834694: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 1280 totalling 1.2KiB
2019-10-27 12:36:48.834706: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 5 Chunks of size 8192 totalling 40.0KiB
2019-10-27 12:36:48.834715: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 9984 totalling 9.8KiB
2019-10-27 12:36:48.834726: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 27648 totalling 27.0KiB
2019-10-27 12:36:48.834736: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 516096 totalling 504.0KiB
2019-10-27 12:36:48.834747: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 12 Chunks of size 1048576 totalling 12.00MiB
2019-10-27 12:36:48.834759: I tensorflow/core/common_runtime/bfc_allocator.cc:921] Sum Total of in-use chunks: 12.57MiB
2019-10-27 12:36:48.834769: I tensorflow/core/common_runtime/bfc_allocator.cc:923] total_region_allocated_bytes_: 4837081088 memory_limit_: 4837081088 available bytes: 0 curr_region_allocation_bytes_: 9674162176
2019-10-27 12:36:48.834784: I tensorflow/core/common_runtime/bfc_allocator.cc:929] Stats:
Limit: 4837081088
InUse: 13185792
MaxInUse: 14756864
NumAllocs: 186
MaxAllocSize: 1048576
你可以看到我的模型很小，它不需要接近 8GB 的任何东西。
编辑#2：
我刚刚恢复到 TF2 测试版 (tensorflow-gpu==2.0.0-beta1)，问题就消失了。希望我们能找到比这更好的解决方案。
这是 TensorFlow 的默认行为，分配的比它实际需要的多 - 虽然它可能不完全是正在分配的 数据集 ，你只需要模型和直接 tensors/data 在 TF/Keras 会话中，在 TF2 中完成通过：
max_memory = 8000 # dedicated memory in MB; run 'dxdiag' to get exact figure
max_usage = 0.95 * max_memory # example for using up to 95%
gpus = tf.config.experimental.list_physical_devices('GPU')
tf.config.experimental.set_virtual_device_configuration(
gpus[0],
[tf.config.experimental.VirtualDeviceConfiguration(memory_limit=max_usage)])
另请参阅 limiting GPU memory growth, and relevant Git 上的 TensorFlow 文档。
更新：TF2 eager 似乎有一个已知的内存管理问题 - 作为解决方法，禁用它在 Eager 中工作，这可以 运行 显着更快 - 请参阅:
tf.compat.v1.disable_eager_execution()
我正在使用 keras API、tensorflow 后端在几个 GB 数据集上训练 LSTM。当 运行 Model.fit() 对一些内存数据 (numpy) 时，它会在一个请求中分配 8GB 内存，这在仅加载一小部分数据时不会发生。我的 GPU 不能同时使用模型参数和 8GB，它会耗尽内存并停止。我很确定这在我从 TF2 beta 升级到 TF2rc 后开始发生。我是这样称呼适合的：
tb = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
es = keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=patience*2, restore_best_weights=True)
lr_reduce = keras.callbacks.ReduceLROnPlateau(factor=0.1, patience=patience, verbose=1)
chkpointing = keras.callbacks.ModelCheckpoint(weight_fname, monitor='val_loss', verbose=0, save_best_only=True,
save_weights_only=True, mode='auto')
model.fit(train_data_x, train_data_y, validation_data=(test_data_x, test_data_y), batch_size=cfg['batch_size'],
epochs=nepochs, validation_freq=1, callbacks=[lr_reduce, es, tb, chkpointing],
class_weight=cfg['class_weight'], shuffle=True)
是否打算在 GPU 上为整个数据集分配 space？我怎样才能防止它发生？
编辑：
更新了代码以限制内存分配。它确实限制了它，因为它表明 TF 可以访问比以前更少的内存，但它仍然尝试分配 8.14GB。这是我限制内存和 select GPU 的方法：
def select_gpu(gpu_id=-1, max_usage=.5): # max 2 gpu only
os.environ["CUDA_VISIBLE_DEVICES"] = str(gpu_id) if gpu_id != -1 else '0,1'
gpus = tf.config.experimental.list_physical_devices('GPU')
max_memory = 11534 # MB got from: grep -i --color memory /var/log/Xorg.0.log
for gpu in gpus:
print('GPU FOUND:', gpu)
tf.config.experimental.set_memory_growth(gpu, True) # FIXME true
tf.config.experimental.set_virtual_device_configuration(gpu,
[tf.config.experimental.VirtualDeviceConfiguration(memory_limit=max_memory * max_usage)])
print('RUNNING ON GPU #{}'.format(gpu_id))
# ... just call select_gpu(0) in the beginning of the script
这是错误：
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
time_distributed (TimeDistri (None, 42, 256) 7168
_________________________________________________________________
cu_dnnlstm (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_1 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_2 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_3 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_4 (CuDNNLSTM) (None, 42, 256) 526336
_________________________________________________________________
cu_dnnlstm_5 (CuDNNLSTM) (None, 256) 526336
_________________________________________________________________
dense_1 (Dense) (None, 256) 65792
_________________________________________________________________
dense_2 (Dense) (None, 1) 257
=================================================================
Total params: 3,231,233
Trainable params: 3,231,233
Non-trainable params: 0
_________________________________________________________________
None
2019-10-27 12:36:48.833843: W tensorflow/core/common_runtime/bfc_allocator.cc:419] Allocator (GPU_0_bfc) ran out of memory trying to allocate 8.14GiB (rounded to 8738821888). Current allocation summary follows.
2019-10-27 12:36:48.833927: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (256): Total Chunks: 16, Chunks in use: 15. 4.0KiB allocated for chunks. 3.8KiB in use in bin. 72B client-requested in use in bin.
2019-10-27 12:36:48.833944: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (512): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.833958: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (1024): Total Chunks: 5, Chunks in use: 4. 5.5KiB allocated for chunks. 4.2KiB in use in bin. 4.0KiB client-requested in use in bin.
2019-10-27 12:36:48.833970: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (2048): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.833982: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (4096): Total Chunks: 1, Chunks in use: 0. 4.8KiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.833998: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (8192): Total Chunks: 6, Chunks in use: 6. 49.8KiB allocated for chunks. 49.8KiB in use in bin. 48.0KiB client-requested in use in bin.
2019-10-27 12:36:48.834012: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (16384): Total Chunks: 1, Chunks in use: 1. 27.0KiB allocated for chunks. 27.0KiB in use in bin. 27.0KiB client-requested in use in bin.
2019-10-27 12:36:48.834023: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (32768): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834034: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (65536): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834045: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (131072): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834060: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (262144): Total Chunks: 1, Chunks in use: 1. 504.0KiB allocated for chunks. 504.0KiB in use in bin. 256.0KiB client-requested in use in bin.
2019-10-27 12:36:48.834073: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (524288): Total Chunks: 1, Chunks in use: 0. 512.0KiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834088: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (1048576): Total Chunks: 12, Chunks in use: 12. 12.00MiB allocated for chunks. 12.00MiB in use in bin. 12.00MiB client-requested in use in bin.
2019-10-27 12:36:48.834099: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (2097152): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834110: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (4194304): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834122: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (8388608): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834132: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (16777216): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834143: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (33554432): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834156: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (67108864): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834167: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (134217728): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834180: I tensorflow/core/common_runtime/bfc_allocator.cc:869] Bin (268435456): Total Chunks: 1, Chunks in use: 0. 4.49GiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-10-27 12:36:48.834193: I tensorflow/core/common_runtime/bfc_allocator.cc:885] Bin for 8.14GiB was 256.00MiB, Chunk State:
2019-10-27 12:36:48.834213: I tensorflow/core/common_runtime/bfc_allocator.cc:891] Size: 4.49GiB | Requested Size: 1.00MiB | in_use: 0 | bin_num: 20, prev: Size: 1.00MiB | Requested Size: 1.00MiB | in_use: 1 | bin_num: -1
2019-10-27 12:36:48.834223: I tensorflow/core/common_runtime/bfc_allocator.cc:898] Next region of size 4837081088
2019-10-27 12:36:48.834237: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000000 next 1 of size 256
2019-10-27 12:36:48.834247: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000100 next 2 of size 256
2019-10-27 12:36:48.834257: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000200 next 3 of size 1280
2019-10-27 12:36:48.834267: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000700 next 4 of size 256
2019-10-27 12:36:48.834277: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000800 next 5 of size 1024
2019-10-27 12:36:48.834287: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000c00 next 8 of size 256
2019-10-27 12:36:48.834296: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000d00 next 9 of size 256
2019-10-27 12:36:48.834306: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000e00 next 10 of size 256
2019-10-27 12:36:48.834316: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6000f00 next 13 of size 256
2019-10-27 12:36:48.834325: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001000 next 34 of size 256
2019-10-27 12:36:48.834335: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001100 next 35 of size 256
2019-10-27 12:36:48.834344: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001200 next 37 of size 256
2019-10-27 12:36:48.834354: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001300 next 16 of size 256
2019-10-27 12:36:48.834363: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001400 next 14 of size 256
2019-10-27 12:36:48.834373: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6001500 next 40 of size 1280
2019-10-27 12:36:48.834382: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6001a00 next 41 of size 1024
2019-10-27 12:36:48.834392: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6001e00 next 18 of size 4864
2019-10-27 12:36:48.834402: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6003100 next 19 of size 8192
2019-10-27 12:36:48.834411: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005100 next 36 of size 1024
2019-10-27 12:36:48.834420: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005500 next 39 of size 256
2019-10-27 12:36:48.834430: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005600 next 42 of size 256
2019-10-27 12:36:48.834439: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005700 next 43 of size 256
2019-10-27 12:36:48.834449: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6005800 next 21 of size 256
2019-10-27 12:36:48.834459: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6005900 next 22 of size 8192
2019-10-27 12:36:48.834469: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6007900 next 25 of size 8192
2019-10-27 12:36:48.834478: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6009900 next 28 of size 8192
2019-10-27 12:36:48.834488: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf600b900 next 6 of size 9984
2019-10-27 12:36:48.834500: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf600e000 next 7 of size 27648
2019-10-27 12:36:48.834509: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6014c00 next 33 of size 8192
2019-10-27 12:36:48.834519: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6016c00 next 38 of size 524288
2019-10-27 12:36:48.834528: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6096c00 next 17 of size 516096
2019-10-27 12:36:48.834538: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6114c00 next 12 of size 1048576
2019-10-27 12:36:48.834548: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6214c00 next 11 of size 1048576
2019-10-27 12:36:48.834558: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6314c00 next 20 of size 1048576
2019-10-27 12:36:48.834567: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6414c00 next 15 of size 1048576
2019-10-27 12:36:48.834577: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6514c00 next 24 of size 1048576
2019-10-27 12:36:48.834586: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6614c00 next 23 of size 1048576
2019-10-27 12:36:48.834595: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6714c00 next 27 of size 1048576
2019-10-27 12:36:48.834605: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6814c00 next 26 of size 1048576
2019-10-27 12:36:48.834614: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6914c00 next 30 of size 1048576
2019-10-27 12:36:48.834623: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6a14c00 next 29 of size 1048576
2019-10-27 12:36:48.834633: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6b14c00 next 32 of size 1048576
2019-10-27 12:36:48.834642: I tensorflow/core/common_runtime/bfc_allocator.cc:905] InUse at 0x7f3cf6c14c00 next 31 of size 1048576
2019-10-27 12:36:48.834652: I tensorflow/core/common_runtime/bfc_allocator.cc:905] Free at 0x7f3cf6d14c00 next 18446744073709551615 of size 4823364608
2019-10-27 12:36:48.834661: I tensorflow/core/common_runtime/bfc_allocator.cc:914] Summary of in-use Chunks by size:
2019-10-27 12:36:48.834673: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 15 Chunks of size 256 totalling 3.8KiB
2019-10-27 12:36:48.834684: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 3 Chunks of size 1024 totalling 3.0KiB
2019-10-27 12:36:48.834694: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 1280 totalling 1.2KiB
2019-10-27 12:36:48.834706: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 5 Chunks of size 8192 totalling 40.0KiB
2019-10-27 12:36:48.834715: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 9984 totalling 9.8KiB
2019-10-27 12:36:48.834726: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 27648 totalling 27.0KiB
2019-10-27 12:36:48.834736: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 1 Chunks of size 516096 totalling 504.0KiB
2019-10-27 12:36:48.834747: I tensorflow/core/common_runtime/bfc_allocator.cc:917] 12 Chunks of size 1048576 totalling 12.00MiB
2019-10-27 12:36:48.834759: I tensorflow/core/common_runtime/bfc_allocator.cc:921] Sum Total of in-use chunks: 12.57MiB
2019-10-27 12:36:48.834769: I tensorflow/core/common_runtime/bfc_allocator.cc:923] total_region_allocated_bytes_: 4837081088 memory_limit_: 4837081088 available bytes: 0 curr_region_allocation_bytes_: 9674162176
2019-10-27 12:36:48.834784: I tensorflow/core/common_runtime/bfc_allocator.cc:929] Stats:
Limit: 4837081088
InUse: 13185792
MaxInUse: 14756864
NumAllocs: 186
MaxAllocSize: 1048576
你可以看到我的模型很小，它不需要接近 8GB 的任何东西。
编辑#2：
我刚刚恢复到 TF2 测试版 (tensorflow-gpu==2.0.0-beta1)，问题就消失了。希望我们能找到比这更好的解决方案。
这是 TensorFlow 的默认行为，分配的比它实际需要的多 - 虽然它可能不完全是正在分配的 数据集 ，你只需要模型和直接 tensors/data 在 TF/Keras 会话中，在 TF2 中完成通过：
max_memory = 8000 # dedicated memory in MB; run 'dxdiag' to get exact figure
max_usage = 0.95 * max_memory # example for using up to 95%
gpus = tf.config.experimental.list_physical_devices('GPU')
tf.config.experimental.set_virtual_device_configuration(
gpus[0],
[tf.config.experimental.VirtualDeviceConfiguration(memory_limit=max_usage)])
另请参阅 limiting GPU memory growth, and relevant Git 上的 TensorFlow 文档。
更新：TF2 eager 似乎有一个已知的内存管理问题 - 作为解决方法，禁用它在 Eager 中工作，这可以 运行 显着更快 - 请参阅
tf.compat.v1.disable_eager_execution()