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requirements_lock_3_10.txt
--hash=sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519 \ --hash=sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561 # via requests dill==0.3.7 \ --hash=sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e \ --hash=sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03 # via -r requirements.in dm-tree==0.1.8 \
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tensorflow/c/eager/c_api_experimental.cc
return context->GetContextId(); } void TFE_MonitoringCounterCellIncrementBy(TFE_MonitoringCounterCell* cell, int64_t value) { cell->cell.IncrementBy(value); } int64_t TFE_MonitoringCounterCellValue(TFE_MonitoringCounterCell* cell) { return cell->cell.value(); } TFE_MonitoringCounter0* TFE_MonitoringNewCounter0(const char* name,
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Apr 11 23:52:39 GMT 2024 - 35.9K bytes - Viewed (3) -
requirements_lock_3_11.txt
--hash=sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519 \ --hash=sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561 # via requests dill==0.3.7 \ --hash=sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e \ --hash=sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03 # via -r requirements.in dm-tree==0.1.8 \
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tensorflow/c/eager/BUILD
"tfe_monitoring_reader_internal.h", ], visibility = ["//tensorflow:internal"], deps = [ ":c_api", "//tensorflow/c:c_api", "//tensorflow/core/lib/monitoring:cell_reader", "@com_google_absl//absl/memory", ], alwayslink = 1, ) tf_cuda_cc_test( name = "c_api_experimental_test", size = "small", srcs = [
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RELEASE.md
* tf.optimizers => tf.keras.optimizers * Add tf.keras.layers.AbstractRNNCell as the preferred implementation of RNN cell for TF v2. User can use it to implement RNN cell with custom behavior. * Adding `clear_losses` API to be able to clear losses at the end of forward pass in a custom training loop in eager.
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ci/official/utilities/code_check_full.bats
//tensorflow/python/debug:grpc_tensorflow_server.par //tensorflow/python/feature_column:vocabulary_testdata //tensorflow/python/util:nest_test_main_lib //tensorflow/lite/experimental/examples/lstm:rnn_cell //tensorflow/lite/experimental/examples/lstm:rnn_cell.py //tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test //tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test.py //tensorflow/lite/python:interpreter
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requirements_lock_3_12.txt
--hash=sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519 \ --hash=sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561 # via requests dill==0.3.7 \ --hash=sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e \ --hash=sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03 # via -r requirements.in dm-tree==0.1.8 \
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requirements_lock_3_9.txt
--hash=sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519 \ --hash=sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561 # via requests dill==0.3.7 \ --hash=sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e \ --hash=sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03 # via -r requirements.in dm-tree==0.1.8 \
Plain Text - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Apr 12 04:38:53 GMT 2024 - 44.2K bytes - Viewed (0)