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Functions280 in github.com/cybertronai/gradient-checkpointing

⨍ Functions 280◇ Types & classes 7↳ Endpoints 2
Functionconcat_elu
like concatenated ReLU (http://arxiv.org/abs/1603.05201), but then with ELU
test/pixel_cnn_pp/nn.py:12
Functiondebug_print
Like logger.log, but also replaces all TensorFlow ops/tensors with their names. Sensitive to value of DEBUG_LOGGING, see enable_debug/disable_debug
test/util.py:55
Functiondebug_print2
Like logger.log, but also replaces all TensorFlow ops/tensors with their names. Not sensitive to value of DEBUG_LOGGING Usage: debug_print2("
test/util.py:68
Functiondisable_debug
Turn off debug logging.
test/util.py:35
Methoddiscard
(self, x)
test/linearize.py:293
Functiondiscretized_mix_logistic_loss
log-likelihood for mixture of discretized logistics, assumes the data has been rescaled to [-1,1] interval
test/pixel_cnn_pp/nn.py:46
Functiondown_right_shifted_conv2d
(x, num_filters, filter_size=[2,2], stride=[1,1], **kwargs)
test/pixel_cnn_pp/nn.py:312
Functiondown_right_shifted_deconv2d
(x, num_filters, filter_size=[2,2], stride=[1,1], **kwargs)
test/pixel_cnn_pp/nn.py:317
Functiondown_shift
(x)
test/pixel_cnn_pp/nn.py:292
Functiondown_shifted_conv2d
(x, num_filters, filter_size=[2,3], stride=[1,1], **kwargs)
test/pixel_cnn_pp/nn.py:301
Functiondown_shifted_deconv2d
(x, num_filters, filter_size=[2,3], stride=[1,1], **kwargs)
test/pixel_cnn_pp/nn.py:306
Functionenable_debug
Turn on debug logging.
test/util.py:29
Functionenergy_distance
(x, x_sample)
test/pixel_cnn_pp/nn.py:30
Functionfirst_key
(x)
test/mem_util.py:108
Functiongated_resnet
(x, a=None, h=None, nonlinearity=concat_elu, conv=conv2d, init=False, counters={}, ema=None, dropout_p=0., **k
test/pixel_cnn_pp/nn.py:265
Functionget_execution_order
Return deterministic execution order which approximately minimizes peak memory usage. Args: targets: specifies list of computation Tensor or o
test/linearize.py:402
Methodget_observation_size
(self)
test/data/imagenet_data.py:107
Functionget_vars_maybe_avg
utility for retrieving polyak averaged params
test/pixel_cnn_pp/nn.py:118
Functiongradients_auto
(ys, xs, grad_ys=None, **kwargs)
test/imagenet_test.py:199
Functiongradients_auto
(ys, xs, grad_ys=None, **kwargs)
test/imagenet_correctness_test.py:167
Functiongradients_collection
(ys, xs, grad_ys=None, **kwargs)
memory_saving_gradients.py:39
Functiongradients_collection
(ys, xs, grad_ys=None, **kwargs)
test/resnet_correctness_test.py:244
Functiongradients_collection
(ys, xs, grad_ys=None, **kwargs)
test/resnet_test.py:206
Functiongradients_memory
(ys, xs, grad_ys=None, **kwargs)
memory_saving_gradients.py:36
Functiongradients_memory
(ys, xs, grad_ys=None, **kwargs)
test/deep_resnet_benchmark.py:183
Functiongradients_memory
(ys, xs, grad_ys=None, **kwargs)
test/resnet_correctness_test.py:198
Functiongradients_memory
(ys, xs, grad_ys=None, **kwargs)
test/resnet_test.py:160
Functiongradients_memory
(ys, xs, grad_ys=None, **kwargs)
test/deep_imagenet_benchmark.py:170
Functiongradients_speed
(ys, xs, grad_ys=None, **kwargs)
memory_saving_gradients.py:33
Functiongrads
(ys, xs, grad_ys=None, **kwargs)
test/mnist_correctness_test.py:244
Functiongraphs_isomorphic
Check if two graphs are isomorphic.
test/util.py:120
Functionintercept_op_creation
Drops into PDB when particular op type is added to graph.
test/util.py:378
Functionmake_caterpillar_graph
Length is number of concats.
test/util.py:133
Functionmake_chain_minmax
Creates chain of nodes alternating minimum/maximum.
test/memory_test.py:70
Functionmake_chain_tanh_fill
Creates chain of length length. First node is Variable, rest are tanh. Returns nodes. Note, if length is 1, there are no non-linearities in the gr
test/util.py:202
Functionmake_resnet_custom
Creates resnet-like chain of length length. First node is constant, rest are tanh. Returns list of nodes. Has length - 2 articulation points (ie
test/util.py:237
Functionmodel_spec
We receive a Tensor x of shape (N,H,W,D1) (e.g. (12,32,32,3)) and produce a Tensor x_out of shape (N,H,W,D2) (e.g. (12,32,32,100)), where eac
test/pixel_cnn_pp/model.py:10
Functionmy_apply_op
(obj, op_type_name, name=None, **keywords)
test/util.py:382
Functionnode_name
(node)
test/linearize.py:346
Functionparents_with_controls
(op)
test/linearize.py:62
Functionpick_every_k
Picks out every k'th element from the sequence, using round() when k is not integer.
test/util.py:327
Functionpick_n_equispaced
Picks out n points out of list, at roughly equal intervals.
test/util.py:340
Functionprint_graph
Prints tensorflow graph in dictionary form.
test/linearize.py:260
Functionprint_memory_timeline
Human readable timeline of memory allocation/deallocation for given device. If device is None, prints timeline of the device with highest memory u
test/mem_util.py:174
Functionprint_ops
(ops)
test/linearize.py:113
Functionprint_tf_graph
Prints tensorflow graph in dictionary form.
test/util.py:81
Methodremove
(self, x)
test/linearize.py:297
Functionreport_memory
Helper utility to print 2 memory stats side by side, used in memory tests.
test/util.py:18
Functionresnet_v2
Returns the ResNet model for a given size and number of output classes.
test/resnet_model.py:477
Functionright_shift
(x)
test/pixel_cnn_pp/nn.py:296
Functionrun_all_tests
(module)
test/linearize_test.py:139
Functionsample_from_discretized_mix_logistic
(l,nr_mix)
test/pixel_cnn_pp/nn.py:89
Functionsave_tf_graph
Prints tensorflow graph in dictionary form.
test/util.py:88
Functionsessrun
(*args, **kwargs)
test/imagenet_correctness_test.py:67
Functionset_equal
Converts inputs to sets, tests for equality.
test/util.py:127
Functionsort
Sorts nodes according to order provided. Args: nodes: nodes to sort total_order: list of nodes in correct order dedup: if True, also
test/util.py:353
Functionsorted_articulation_points
Returns list of articulation points (cut vertices) sorted in according to the execution order provided by linearize.
test/linearize.py:510
Functionsubtree_memory
(node)
test/linearize.py:349
Functiontest_caterpillar_linearize
()
test/linearize_test.py:84
Functiontest_chain_tarjan
Like test_chain, but use automatic rewriting with checkpoints="tarjan" strategy.
test/memory_test.py:320
Functiontest_cifar_resnet_grads
()
test/linearize_test.py:249
Functiontest_cifar_resnet_loss
()
test/linearize_test.py:232
Functiontest_cifar_resnet_unmodifed
()
test/linearize_test.py:203
Functiontest_dependent_targets
()
test/linearize_test.py:323
Functiontest_dependent_targets_easy
()
test/linearize_test.py:311
Functiontest_long_chain_tarjan
Like test_chain, but use automatic rewriting with checkpoints="tarjan" strategy.
test/memory_test.py:388
Functiontest_long_resnet_rewrite_tarjan
(linearize=False)
test/memory_test.py:577
Functiontest_memory_method_saves_memory
()
test/resnet_correctness_test.py:190
Functiontest_memory_method_saves_memory
()
test/resnet_test.py:152
Functiontest_print
Should print: leaf1 -> merge1 leaf0 -> merge0 merge1 -> merge2 merge0 -> merge1 leaf2 -> merge2 leaf0/shape -> leaf0 leaf1/shape -> leaf
test/linearize_test.py:24
Functiontest_prune
()
test/linearize_test.py:335
Functiontest_resnet
()
test/memory_test.py:453
Functiontest_resnet_rewrite_tarjan
(linearize=False)
test/memory_test.py:645
Functiontest_reversed_graph
()
test/linearize_test.py:266
Functiontest_targets
()
test/linearize_test.py:110
Functiontest_variables
()
test/linearize_test.py:130
Functiontf_ops_to_nx_graph
Convert Tensorflow graph to NetworkX graph.
test/util.py:107
Functiontiny_cifar10_resnet_v2_generator
Generator for CIFAR-10 ResNet v2 models. Args: resnet_size: A single integer for the size of the ResNet model. num_classes: The number of p
test/resnet_model.py:285
Functiontiny_resnet_v2
Returns the ResNet model for a given size and number of output classes.
test/resnet_model.py:495
Functionto_ops
(iterable)
test/util.py:372
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