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Functions2,488 in github.com/TPCD/LifelongReID

⨍ Functions 2,488◇ Types & classes 338↳ Endpoints 1

apex/apex/pyprof/prof/normalization.py:43

apex/apex/pyprof/prof/conv.py:222

apex/apex/pyprof/prof/activation.py:39

apex/apex/pyprof/prof/embedding.py:69

apex/apex/pyprof/prof/randomSample.py:41

apex/apex/pyprof/prof/convert.py:57

apex/tests/distributed/DDP/ddp_race_condition_test.py:33

apex/tests/L0/run_optimizers/test_dist_adam.py:19

apex/tests/L0/run_amp/test_larc.py:19

apex/tests/L0/run_amp/test_fused_sgd.py:37

apex/tests/L0/run_amp/test_multiple_models_optimizers_losses.py:27

apex/tests/L0/run_amp/test_cache.py:33

apex/tests/L0/run_amp/test_cache.py:46

apex/tests/L0/run_amp/test_cache.py:59

apex/tests/L0/run_amp/test_add_param_group.py:27

apex/tests/L0/run_amp/test_checkpointing.py:21

apex/tests/L0/run_fp16util/test_fp16util.py:16

apex/tests/L0/run_fp16util/test_fp16util.py:29

apex/tests/L0/run_fp16util/test_fp16util.py:45

(ctx, x, z, s, b, rm, riv, mini_m, mini_riv, grid_dim_y, ret_cta, mom, epsilon, is_train, bn_group, my_data, p

apex/apex/contrib/groupbn/batch_norm.py:55

(self, x, z=None)

apex/apex/contrib/groupbn/batch_norm.py:196

(ctx, logits, labels, smoothing=0.0, padding_idx=0, half_to_float=False)

apex/apex/contrib/xentropy/softmax_xentropy.py:6

Input shape: Time x Batch x Channel Self-attention can be implemented by passing in the same arguments for query, key and value. Futu

apex/apex/contrib/multihead_attn/encdec_multihead_attn.py:98

(ctx, use_time_mask, is_training, heads, inputs, input_weights, output_weights, input_biases, output_biases, p

apex/apex/contrib/multihead_attn/fast_self_multihead_attn_func.py:8

(ctx, use_time_mask, is_training, heads, scale, inputs, input_weights, output_weights,

apex/apex/contrib/multihead_attn/self_multihead_attn_func.py:6

(ctx, is_training, heads, inputs, pad_mask, mask_additive, dropout_prob)

apex/apex/contrib/multihead_attn/mask_softmax_dropout_func.py:8

(ctx, use_time_mask, is_training, heads, inputs_q, inputs_kv, lyr_nrm_gamma_weights, lyr_nrm_beta_weights, inp

apex/apex/contrib/multihead_attn/fast_encdec_multihead_attn_norm_add_func.py:14

(ctx, use_time_mask, is_training, heads, inputs, lyr_nrm_gamma_weights, lyr_nrm_beta_weights, input_weights, o

apex/apex/contrib/multihead_attn/fast_self_multihead_attn_norm_add_func.py:7

(ctx, use_time_mask, is_training, heads, scale, inputs_q, inputs_kv, input_weights_q, input_we

apex/apex/contrib/multihead_attn/encdec_multihead_attn_func.py:7

Input shape: Time x Batch x Channel Self-attention can be implemented by passing in the same arguments for query, key and value. Futu

apex/apex/contrib/multihead_attn/self_multihead_attn.py:124

(ctx, use_time_mask, is_training, heads, inputs_q, inputs_kv, input_weights_q, input_weights_kv, output_weight

apex/apex/contrib/multihead_attn/fast_encdec_multihead_attn_func.py:7

(ctx, x, gamma, beta, epsilon)

apex/apex/contrib/layer_norm/layer_norm.py:8

apex/apex/contrib/layer_norm/layer_norm.py:43

apex/apex/RNN/RNNBackend.py:37

apex/apex/RNN/RNNBackend.py:122

forward() if not inited or bsz has changed this will create hidden states

apex/apex/RNN/RNNBackend.py:348

mLSTMRNNCell.forward()

apex/apex/RNN/cells.py:26

(ctx, bias, activation, *args)

apex/apex/mlp/mlp.py:10

apex/apex/fp16_utils/fp16util.py:18

(self, *inputs)

apex/apex/fp16_utils/fp16util.py:82

(ctx, input, z, weight, bias, running_mean, running_variance, eps, track_running_stats = True, momentum = 1.0,

apex/apex/parallel/optimized_sync_batchnorm_kernel.py:10

(ctx, input, weight, bias, running_mean, running_variance, eps, process_group, world_size)

apex/apex/parallel/sync_batchnorm_kernel.py:10

(self, input, z = None)

apex/apex/parallel/optimized_sync_batchnorm.py:70

apex/apex/parallel/sync_batchnorm.py:68

(self, *inputs, **kwargs)

apex/apex/parallel/distributed.py:559

(ctx, input, weight, bias, normalized_shape, eps)

apex/apex/normalization/fused_layer_norm.py:15

(ctx, input, normalized_shape, eps)

apex/apex/normalization/fused_layer_norm.py:42

apex/apex/pyprof/examples/lenet.py:24

apex/apex/pyprof/examples/jit/jit_trace_method.py:13

apex/apex/pyprof/examples/jit/jit_script_method.py:14

apex/apex/pyprof/examples/custom_func_module/custom_module.py:14

(ctx, in1, in2)

apex/apex/pyprof/examples/custom_func_module/custom_function.py:11

apex/apex/pyprof/examples/user_annotation/resnet.py:48

apex/apex/pyprof/examples/user_annotation/resnet.py:158

apex/examples/dcgan/main_amp.py:150

apex/examples/dcgan/main_amp.py:189

lreid/methods/drop_grad.py:19

lreid/methods/backbone.py:26

lreid/methods/backbone.py:40

lreid/methods/backbone.py:50

lreid/methods/backbone.py:64

lreid/methods/backbone.py:84

lreid/methods/backbone.py:120

lreid/methods/backbone.py:167

lreid/methods/backbone.py:221

lreid/methods/backbone.py:258

lreid/models/bnneck.py:40

lreid/models/bnneck.py:64

lreid/models/bnneck.py:88

(self, inputs, adj)

lreid/models/metagraph_fd.py:34

lreid/models/metagraph_fd.py:85

lreid/models/metagraph_fd.py:158

lreid/models/LwFnet.py:39

(self, x, current_step=0)

lreid/models/LwFnet.py:87

(self, x, current_step)

lreid/models/LwFnet.py:164

(self, x, current_step)

lreid/models/LwFnet.py:230

(self, means, variances)

lreid/losses/loss.py:11

Args: inputs: prediction matrix (before softmax) with shape (batch_size, num_classes) targets: ground truth labels with shape (num_classes)

lreid/losses/loss.py:41

(self, global_feat1, global_feat2, global_feat3, labels1, labels2, labels3)

lreid/losses/ranked_list_loss.py:79

Functionfused_layer_norm

(input, normalized_shape, eps=1e-6)

apex/apex/normalization/fused_layer_norm.py:67

Functionfused_layer_norm_affine

(input, normalized_shape, weight, bias, eps=1e-6)

apex/apex/normalization/fused_layer_norm.py:64

apex/apex/contrib/csrc/multihead_attn/self_multihead_attn.cpp:39

apex/apex/contrib/csrc/multihead_attn/self_multihead_attn_norm_add.cpp:47

apex/apex/contrib/csrc/multihead_attn/encdec_multihead_attn.cpp:43

apex/apex/contrib/csrc/multihead_attn/self_multihead_attn_bias.cpp:43

apex/apex/contrib/csrc/multihead_attn/self_multihead_attn_bias_additive_mask.cpp:46

apex/apex/contrib/csrc/multihead_attn/masked_softmax_dropout.cpp:31

apex/apex/contrib/csrc/multihead_attn/additive_masked_softmax_dropout.cpp:31

apex/apex/contrib/csrc/multihead_attn/encdec_multihead_attn_norm_add.cpp:52

apex/apex/contrib/csrc/groupbn/batch_norm_add_relu.h:598

MethodfwdInference

apex/apex/contrib/csrc/groupbn/batch_norm.h:569

MethodfwdInference

apex/apex/contrib/csrc/groupbn/batch_norm_add_relu.h:515

Functionfwd_wrapper

(*fargs, **fkwargs)

apex/apex/amp/wrap.py:183

Methodgen_mixed_grad

(self, ref_param, tst_param, scale=1.0)

apex/tests/L0/run_optimizers/test_lamb.py:175

MethodgetLayerName

Get layer names from layer marker list.

apex/apex/pyprof/parse/nvvp.py:137

MethodgetPointer

apex/apex/contrib/csrc/multihead_attn/layer_norm.h:268

Get sequence ids from seq / alt seq marker list.

apex/apex/pyprof/parse/nvvp.py:149

Functionget_cuda_version

apex/apex/amp/utils.py:11

Methodget_last_lr

Return last computed learning rate by current scheduler.

lreid/core/torch16_lr_scheduler.py:97

lreid/core/torch16_lr_scheduler.py:229

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