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akita train error #200

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guandailu opened this issue Jul 31, 2024 · 0 comments
Open

akita train error #200

guandailu opened this issue Jul 31, 2024 · 0 comments

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@guandailu
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I am running the Akita tutorial, but I have the following errors:

2024-07-30 09:37:31.023852: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Model: "model_1"

Layer (type) Output Shape Param # Connected to

sequence (InputLayer) [(None, 1048576, 4)] 0

stochastic_reverse_complement ( ((None, 1048576, 4), 0 sequence[0][0]

stochastic_shift (StochasticShi (None, 1048576, 4) 0 stochastic_reverse_complement[0][

re_lu (ReLU) (None, 1048576, 4) 0 stochastic_shift[0][0]

conv1d (Conv1D) (None, 1048576, 96) 4224 re_lu[0][0]

batch_normalization (BatchNorma (None, 1048576, 96) 384 conv1d[0][0]

max_pooling1d (MaxPooling1D) (None, 524288, 96) 0 batch_normalization[0][0]

re_lu_1 (ReLU) (None, 524288, 96) 0 max_pooling1d[0][0]

conv1d_1 (Conv1D) (None, 524288, 96) 46080 re_lu_1[0][0]

batch_normalization_1 (BatchNor (None, 524288, 96) 384 conv1d_1[0][0]

max_pooling1d_1 (MaxPooling1D) (None, 262144, 96) 0 batch_normalization_1[0][0]

re_lu_2 (ReLU) (None, 262144, 96) 0 max_pooling1d_1[0][0]

conv1d_2 (Conv1D) (None, 262144, 96) 46080 re_lu_2[0][0]

batch_normalization_2 (BatchNor (None, 262144, 96) 384 conv1d_2[0][0]

max_pooling1d_2 (MaxPooling1D) (None, 131072, 96) 0 batch_normalization_2[0][0]

re_lu_3 (ReLU) (None, 131072, 96) 0 max_pooling1d_2[0][0]

conv1d_3 (Conv1D) (None, 131072, 96) 46080 re_lu_3[0][0]

batch_normalization_3 (BatchNor (None, 131072, 96) 384 conv1d_3[0][0]

max_pooling1d_3 (MaxPooling1D) (None, 65536, 96) 0 batch_normalization_3[0][0]

re_lu_4 (ReLU) (None, 65536, 96) 0 max_pooling1d_3[0][0]

conv1d_4 (Conv1D) (None, 65536, 96) 46080 re_lu_4[0][0]

batch_normalization_4 (BatchNor (None, 65536, 96) 384 conv1d_4[0][0]

max_pooling1d_4 (MaxPooling1D) (None, 32768, 96) 0 batch_normalization_4[0][0]

re_lu_5 (ReLU) (None, 32768, 96) 0 max_pooling1d_4[0][0]

conv1d_5 (Conv1D) (None, 32768, 96) 46080 re_lu_5[0][0]

batch_normalization_5 (BatchNor (None, 32768, 96) 384 conv1d_5[0][0]

max_pooling1d_5 (MaxPooling1D) (None, 16384, 96) 0 batch_normalization_5[0][0]

re_lu_6 (ReLU) (None, 16384, 96) 0 max_pooling1d_5[0][0]

conv1d_6 (Conv1D) (None, 16384, 96) 46080 re_lu_6[0][0]

batch_normalization_6 (BatchNor (None, 16384, 96) 384 conv1d_6[0][0]

max_pooling1d_6 (MaxPooling1D) (None, 8192, 96) 0 batch_normalization_6[0][0]

re_lu_7 (ReLU) (None, 8192, 96) 0 max_pooling1d_6[0][0]

conv1d_7 (Conv1D) (None, 8192, 96) 46080 re_lu_7[0][0]

batch_normalization_7 (BatchNor (None, 8192, 96) 384 conv1d_7[0][0]

max_pooling1d_7 (MaxPooling1D) (None, 4096, 96) 0 batch_normalization_7[0][0]

re_lu_8 (ReLU) (None, 4096, 96) 0 max_pooling1d_7[0][0]

conv1d_8 (Conv1D) (None, 4096, 96) 46080 re_lu_8[0][0]

batch_normalization_8 (BatchNor (None, 4096, 96) 384 conv1d_8[0][0]

max_pooling1d_8 (MaxPooling1D) (None, 2048, 96) 0 batch_normalization_8[0][0]

re_lu_9 (ReLU) (None, 2048, 96) 0 max_pooling1d_8[0][0]

conv1d_9 (Conv1D) (None, 2048, 96) 46080 re_lu_9[0][0]

batch_normalization_9 (BatchNor (None, 2048, 96) 384 conv1d_9[0][0]

max_pooling1d_9 (MaxPooling1D) (None, 1024, 96) 0 batch_normalization_9[0][0]

re_lu_10 (ReLU) (None, 1024, 96) 0 max_pooling1d_9[0][0]

conv1d_10 (Conv1D) (None, 1024, 96) 46080 re_lu_10[0][0]

batch_normalization_10 (BatchNo (None, 1024, 96) 384 conv1d_10[0][0]

max_pooling1d_10 (MaxPooling1D) (None, 512, 96) 0 batch_normalization_10[0][0]

re_lu_11 (ReLU) (None, 512, 96) 0 max_pooling1d_10[0][0]

conv1d_11 (Conv1D) (None, 512, 48) 13824 re_lu_11[0][0]

batch_normalization_11 (BatchNo (None, 512, 48) 192 conv1d_11[0][0]

re_lu_12 (ReLU) (None, 512, 48) 0 batch_normalization_11[0][0]

conv1d_12 (Conv1D) (None, 512, 96) 4608 re_lu_12[0][0]

batch_normalization_12 (BatchNo (None, 512, 96) 384 conv1d_12[0][0]

dropout (Dropout) (None, 512, 96) 0 batch_normalization_12[0][0]

add (Add) (None, 512, 96) 0 max_pooling1d_10[0][0]
dropout[0][0]

re_lu_13 (ReLU) (None, 512, 96) 0 add[0][0]

conv1d_13 (Conv1D) (None, 512, 48) 13824 re_lu_13[0][0]

batch_normalization_13 (BatchNo (None, 512, 48) 192 conv1d_13[0][0]

re_lu_14 (ReLU) (None, 512, 48) 0 batch_normalization_13[0][0]

conv1d_14 (Conv1D) (None, 512, 96) 4608 re_lu_14[0][0]

batch_normalization_14 (BatchNo (None, 512, 96) 384 conv1d_14[0][0]

dropout_1 (Dropout) (None, 512, 96) 0 batch_normalization_14[0][0]

add_1 (Add) (None, 512, 96) 0 add[0][0]
dropout_1[0][0]

re_lu_15 (ReLU) (None, 512, 96) 0 add_1[0][0]

conv1d_15 (Conv1D) (None, 512, 48) 13824 re_lu_15[0][0]

batch_normalization_15 (BatchNo (None, 512, 48) 192 conv1d_15[0][0]

re_lu_16 (ReLU) (None, 512, 48) 0 batch_normalization_15[0][0]

conv1d_16 (Conv1D) (None, 512, 96) 4608 re_lu_16[0][0]

batch_normalization_16 (BatchNo (None, 512, 96) 384 conv1d_16[0][0]

dropout_2 (Dropout) (None, 512, 96) 0 batch_normalization_16[0][0]

add_2 (Add) (None, 512, 96) 0 add_1[0][0]
dropout_2[0][0]

re_lu_17 (ReLU) (None, 512, 96) 0 add_2[0][0]

conv1d_17 (Conv1D) (None, 512, 48) 13824 re_lu_17[0][0]

batch_normalization_17 (BatchNo (None, 512, 48) 192 conv1d_17[0][0]

re_lu_18 (ReLU) (None, 512, 48) 0 batch_normalization_17[0][0]

conv1d_18 (Conv1D) (None, 512, 96) 4608 re_lu_18[0][0]

batch_normalization_18 (BatchNo (None, 512, 96) 384 conv1d_18[0][0]

dropout_3 (Dropout) (None, 512, 96) 0 batch_normalization_18[0][0]

add_3 (Add) (None, 512, 96) 0 add_2[0][0]
dropout_3[0][0]

re_lu_19 (ReLU) (None, 512, 96) 0 add_3[0][0]

conv1d_19 (Conv1D) (None, 512, 48) 13824 re_lu_19[0][0]

batch_normalization_19 (BatchNo (None, 512, 48) 192 conv1d_19[0][0]

re_lu_20 (ReLU) (None, 512, 48) 0 batch_normalization_19[0][0]

conv1d_20 (Conv1D) (None, 512, 96) 4608 re_lu_20[0][0]

batch_normalization_20 (BatchNo (None, 512, 96) 384 conv1d_20[0][0]

dropout_4 (Dropout) (None, 512, 96) 0 batch_normalization_20[0][0]

add_4 (Add) (None, 512, 96) 0 add_3[0][0]
dropout_4[0][0]

re_lu_21 (ReLU) (None, 512, 96) 0 add_4[0][0]

conv1d_21 (Conv1D) (None, 512, 48) 13824 re_lu_21[0][0]

batch_normalization_21 (BatchNo (None, 512, 48) 192 conv1d_21[0][0]

re_lu_22 (ReLU) (None, 512, 48) 0 batch_normalization_21[0][0]

conv1d_22 (Conv1D) (None, 512, 96) 4608 re_lu_22[0][0]

batch_normalization_22 (BatchNo (None, 512, 96) 384 conv1d_22[0][0]

dropout_5 (Dropout) (None, 512, 96) 0 batch_normalization_22[0][0]

add_5 (Add) (None, 512, 96) 0 add_4[0][0]
dropout_5[0][0]

re_lu_23 (ReLU) (None, 512, 96) 0 add_5[0][0]

conv1d_23 (Conv1D) (None, 512, 48) 13824 re_lu_23[0][0]

batch_normalization_23 (BatchNo (None, 512, 48) 192 conv1d_23[0][0]

re_lu_24 (ReLU) (None, 512, 48) 0 batch_normalization_23[0][0]

conv1d_24 (Conv1D) (None, 512, 96) 4608 re_lu_24[0][0]

batch_normalization_24 (BatchNo (None, 512, 96) 384 conv1d_24[0][0]

dropout_6 (Dropout) (None, 512, 96) 0 batch_normalization_24[0][0]

add_6 (Add) (None, 512, 96) 0 add_5[0][0]
dropout_6[0][0]

re_lu_25 (ReLU) (None, 512, 96) 0 add_6[0][0]

conv1d_25 (Conv1D) (None, 512, 48) 13824 re_lu_25[0][0]

batch_normalization_25 (BatchNo (None, 512, 48) 192 conv1d_25[0][0]

re_lu_26 (ReLU) (None, 512, 48) 0 batch_normalization_25[0][0]

conv1d_26 (Conv1D) (None, 512, 96) 4608 re_lu_26[0][0]

batch_normalization_26 (BatchNo (None, 512, 96) 384 conv1d_26[0][0]

dropout_7 (Dropout) (None, 512, 96) 0 batch_normalization_26[0][0]

add_7 (Add) (None, 512, 96) 0 add_6[0][0]
dropout_7[0][0]

re_lu_27 (ReLU) (None, 512, 96) 0 add_7[0][0]

conv1d_27 (Conv1D) (None, 512, 64) 30720 re_lu_27[0][0]

batch_normalization_27 (BatchNo (None, 512, 64) 256 conv1d_27[0][0]

re_lu_28 (ReLU) (None, 512, 64) 0 batch_normalization_27[0][0]

one_to_two (OneToTwo) (None, 512, 512, 64) 0 re_lu_28[0][0]

concat_dist2d (ConcatDist2D) (None, 512, 512, 65) 0 one_to_two[0][0]

re_lu_29 (ReLU) (None, 512, 512, 65) 0 concat_dist2d[0][0]

conv2d (Conv2D) (None, 512, 512, 48) 28080 re_lu_29[0][0]

batch_normalization_28 (BatchNo (None, 512, 512, 48) 192 conv2d[0][0]

symmetrize2d (Symmetrize2D) (None, 512, 512, 48) 0 batch_normalization_28[0][0]

re_lu_30 (ReLU) (None, 512, 512, 48) 0 symmetrize2d[0][0]

conv2d_1 (Conv2D) (None, 512, 512, 24) 10368 re_lu_30[0][0]

batch_normalization_29 (BatchNo (None, 512, 512, 24) 96 conv2d_1[0][0]

re_lu_31 (ReLU) (None, 512, 512, 24) 0 batch_normalization_29[0][0]

conv2d_2 (Conv2D) (None, 512, 512, 48) 1152 re_lu_31[0][0]

batch_normalization_30 (BatchNo (None, 512, 512, 48) 192 conv2d_2[0][0]

dropout_8 (Dropout) (None, 512, 512, 48) 0 batch_normalization_30[0][0]

add_8 (Add) (None, 512, 512, 48) 0 symmetrize2d[0][0]
dropout_8[0][0]

symmetrize2d_1 (Symmetrize2D) (None, 512, 512, 48) 0 add_8[0][0]

re_lu_32 (ReLU) (None, 512, 512, 48) 0 symmetrize2d_1[0][0]

conv2d_3 (Conv2D) (None, 512, 512, 24) 10368 re_lu_32[0][0]

batch_normalization_31 (BatchNo (None, 512, 512, 24) 96 conv2d_3[0][0]

re_lu_33 (ReLU) (None, 512, 512, 24) 0 batch_normalization_31[0][0]

conv2d_4 (Conv2D) (None, 512, 512, 48) 1152 re_lu_33[0][0]

batch_normalization_32 (BatchNo (None, 512, 512, 48) 192 conv2d_4[0][0]

dropout_9 (Dropout) (None, 512, 512, 48) 0 batch_normalization_32[0][0]

add_9 (Add) (None, 512, 512, 48) 0 symmetrize2d_1[0][0]
dropout_9[0][0]

symmetrize2d_2 (Symmetrize2D) (None, 512, 512, 48) 0 add_9[0][0]

re_lu_34 (ReLU) (None, 512, 512, 48) 0 symmetrize2d_2[0][0]

conv2d_5 (Conv2D) (None, 512, 512, 24) 10368 re_lu_34[0][0]

batch_normalization_33 (BatchNo (None, 512, 512, 24) 96 conv2d_5[0][0]

re_lu_35 (ReLU) (None, 512, 512, 24) 0 batch_normalization_33[0][0]

conv2d_6 (Conv2D) (None, 512, 512, 48) 1152 re_lu_35[0][0]

batch_normalization_34 (BatchNo (None, 512, 512, 48) 192 conv2d_6[0][0]

dropout_10 (Dropout) (None, 512, 512, 48) 0 batch_normalization_34[0][0]

add_10 (Add) (None, 512, 512, 48) 0 symmetrize2d_2[0][0]
dropout_10[0][0]

symmetrize2d_3 (Symmetrize2D) (None, 512, 512, 48) 0 add_10[0][0]

re_lu_36 (ReLU) (None, 512, 512, 48) 0 symmetrize2d_3[0][0]

conv2d_7 (Conv2D) (None, 512, 512, 24) 10368 re_lu_36[0][0]

batch_normalization_35 (BatchNo (None, 512, 512, 24) 96 conv2d_7[0][0]

re_lu_37 (ReLU) (None, 512, 512, 24) 0 batch_normalization_35[0][0]

conv2d_8 (Conv2D) (None, 512, 512, 48) 1152 re_lu_37[0][0]

batch_normalization_36 (BatchNo (None, 512, 512, 48) 192 conv2d_8[0][0]

dropout_11 (Dropout) (None, 512, 512, 48) 0 batch_normalization_36[0][0]

add_11 (Add) (None, 512, 512, 48) 0 symmetrize2d_3[0][0]
dropout_11[0][0]

symmetrize2d_4 (Symmetrize2D) (None, 512, 512, 48) 0 add_11[0][0]

re_lu_38 (ReLU) (None, 512, 512, 48) 0 symmetrize2d_4[0][0]

conv2d_9 (Conv2D) (None, 512, 512, 24) 10368 re_lu_38[0][0]

batch_normalization_37 (BatchNo (None, 512, 512, 24) 96 conv2d_9[0][0]

re_lu_39 (ReLU) (None, 512, 512, 24) 0 batch_normalization_37[0][0]

conv2d_10 (Conv2D) (None, 512, 512, 48) 1152 re_lu_39[0][0]

batch_normalization_38 (BatchNo (None, 512, 512, 48) 192 conv2d_10[0][0]

dropout_12 (Dropout) (None, 512, 512, 48) 0 batch_normalization_38[0][0]

add_12 (Add) (None, 512, 512, 48) 0 symmetrize2d_4[0][0]
dropout_12[0][0]

symmetrize2d_5 (Symmetrize2D) (None, 512, 512, 48) 0 add_12[0][0]

re_lu_40 (ReLU) (None, 512, 512, 48) 0 symmetrize2d_5[0][0]

conv2d_11 (Conv2D) (None, 512, 512, 24) 10368 re_lu_40[0][0]

batch_normalization_39 (BatchNo (None, 512, 512, 24) 96 conv2d_11[0][0]

re_lu_41 (ReLU) (None, 512, 512, 24) 0 batch_normalization_39[0][0]

conv2d_12 (Conv2D) (None, 512, 512, 48) 1152 re_lu_41[0][0]

batch_normalization_40 (BatchNo (None, 512, 512, 48) 192 conv2d_12[0][0]

dropout_13 (Dropout) (None, 512, 512, 48) 0 batch_normalization_40[0][0]

add_13 (Add) (None, 512, 512, 48) 0 symmetrize2d_5[0][0]
dropout_13[0][0]

symmetrize2d_6 (Symmetrize2D) (None, 512, 512, 48) 0 add_13[0][0]

cropping2d (Cropping2D) (None, 448, 448, 48) 0 symmetrize2d_6[0][0]

upper_tri (UpperTri) (None, 99681, 48) 0 cropping2d[0][0]

dense (Dense) (None, 99681, 2) 98 upper_tri[0][0]

switch_reverse_triu (SwitchReve (None, 99681, 2) 0 dense[0][0]
stochastic_reverse_complement[0][

Total params: 751,506
Trainable params: 746,002
Non-trainable params: 5,504

None
model_strides [2048]
target_lengths [99681]
target_crops [-49585]
2024-07-30 09:37:32.487935: I tensorflow/core/profiler/lib/profiler_session.cc:136] Profiler session initializing.
2024-07-30 09:37:32.487981: I tensorflow/core/profiler/lib/profiler_session.cc:155] Profiler session started.
2024-07-30 09:37:32.488016: I tensorflow/core/profiler/lib/profiler_session.cc:172] Profiler session tear down.
2024-07-30 09:37:32.527294: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2024-07-30 09:37:32.527885: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794625000 Hz
Epoch 1/10000
1/3504 [..............................] - ETA: 29:15:00 - loss: 1.7668 - pearsonr: 0.0199 - r2: -7.18172024-07-30 09:38:02.775668: I tensorflow/core/profiler/lib/profiler_session.cc:136] Profiler session initializing.
2024-07-30 09:38:02.775727: I tensorflow/core/profiler/lib/profiler_session.cc:155] Profiler session started.
2/3504 [..............................] - ETA: 20:41:28 - loss: 1.4813 - pearsonr: 0.0338 - r2: -5.04252024-07-30 09:38:23.867246: I tensorflow/core/profiler/lib/profiler_session.cc:71] Profiler session collecting data.
2024-07-30 09:38:23.896953: I tensorflow/core/profiler/lib/profiler_session.cc:172] Profiler session tear down.
2024-07-30 09:38:23.918338: I tensorflow/core/profiler/rpc/client/save_profile.cc:137] Creating directory: ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23
2024-07-30 09:38:23.933617: I tensorflow/core/profiler/rpc/client/save_profile.cc:143] Dumped gzipped tool data for trace.json.gz to ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23/bm15.trace.json.gz
2024-07-30 09:38:23.954239: I tensorflow/core/profiler/rpc/client/save_profile.cc:137] Creating directory: ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23
2024-07-30 09:38:23.956466: I tensorflow/core/profiler/rpc/client/save_profile.cc:143] Dumped gzipped tool data for memory_profile.json.gz to ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23/bm15.memory_profile.json.gz
2024-07-30 09:38:23.967561: I tensorflow/core/profiler/rpc/client/capture_profile.cc:251] Creating directory: ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23Dumped tool data for xplane.pb to ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23/bm15.xplane.pb
Dumped tool data for overview_page.pb to ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23/bm15.overview_page.pb
Dumped tool data for input_pipeline.pb to ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23/bm15.input_pipeline.pb
Dumped tool data for tensorflow_stats.pb to ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23/bm15.tensorflow_stats.pb
Dumped tool data for kernel_stats.pb to ./data/1m/train_out/train/plugins/profile/2024_07_30_09_38_23/bm15.kernel_stats.pb

3504/3504 [==============================] - ETA: 0s - loss: 0.3867 - pearsonr: 0.0205 - r2: -0.1191 Traceback (most recent call last):
File "/group/zhougrp4/dguan/microc/12_modelling/Akita/basenji/bin/akita_train.py", line 182, in
main()
File "/group/zhougrp4/dguan/microc/12_modelling/Akita/basenji/bin/akita_train.py", line 171, in main
seqnn_trainer.fit_keras(seqnn_model)
File "/group/zhougrp4/dguan/microc/12_modelling/Akita/basenji/basenji/trainer.py", line 141, in fit_keras
seqnn_model.model.fit(
File "/group/zhougrp4/dguan/bin/.conda/akita/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1131, in fit
val_logs = self.evaluate(
File "/group/zhougrp4/dguan/bin/.conda/akita/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1384, in evaluate
self.reset_metrics()
File "/group/zhougrp4/dguan/bin/.conda/akita/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1669, in reset_metrics
m.reset_states()
File "/group/zhougrp4/dguan/bin/.conda/akita/lib/python3.8/site-packages/tensorflow/python/keras/metrics.py", line 253, in reset_states
K.batch_set_value([(v, 0) for v in self.variables])
File "/group/zhougrp4/dguan/bin/.conda/akita/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper
return target(*args, **kwargs)
File "/group/zhougrp4/dguan/bin/.conda/akita/lib/python3.8/site-packages/tensorflow/python/keras/backend.py", line 3706, in batch_set_value
x.assign(np.asarray(value, dtype=dtype(x)))
File "/group/zhougrp4/dguan/bin/.conda/akita/lib/python3.8/site-packages/tensorflow/python/ops/resource_variable_ops.py", line 888, in assign
raise ValueError(
ValueError: Cannot assign to variable count:0 due to variable shape (2,) and value shape () are incompatible

My conda environment:
name: akita
channels:

  • nvidia
  • conda-forge
  • bioconda
  • defaults
    dependencies:
  • _libgcc_mutex=0.1=conda_forge
  • _openmp_mutex=4.5=2_gnu
  • abseil-cpp=20200923.3=h9c3ff4c_0
  • absl-py=2.1.0=pyhd8ed1ab_0
  • aiohttp=3.9.5=py38h01eb140_0
  • aiosignal=1.3.1=pyhd8ed1ab_0
  • alsa-lib=1.2.12=h4ab18f5_0
  • anyio=4.4.0=pyhd8ed1ab_0
  • argon2-cffi=23.1.0=pyhd8ed1ab_0
  • argon2-cffi-bindings=21.2.0=py38h01eb140_4
  • arrow=1.3.0=pyhd8ed1ab_0
  • astor=0.8.1=pyh9f0ad1d_0
  • astropy=5.1=py38h7deecbd_0
  • asttokens=2.4.1=pyhd8ed1ab_0
  • astunparse=1.6.3=pyhd8ed1ab_0
  • async-lru=2.0.4=pyhd8ed1ab_0
  • async-timeout=4.0.3=pyhd8ed1ab_0
  • attr=2.5.1=h166bdaf_1
  • attrs=23.2.0=pyh71513ae_0
  • babel=2.14.0=pyhd8ed1ab_0
  • backcall=0.2.0=pyh9f0ad1d_0
  • beautifulsoup4=4.12.3=pyha770c72_0
  • bedtools=2.31.1=hf5e1c6e_2
  • blas=1.0=openblas
  • bleach=6.1.0=pyhd8ed1ab_0
  • blinker=1.8.2=pyhd8ed1ab_0
  • bottleneck=1.3.7=py38ha9d4c09_0
  • brotli=1.0.9=h5eee18b_8
  • brotli-bin=1.0.9=h5eee18b_8
  • brotli-python=1.0.9=py38h6a678d5_8
  • bzip2=1.0.8=h5eee18b_6
  • c-ares=1.32.3=h4bc722e_0
  • ca-certificates=2024.7.4=hbcca054_0
  • cached-property=1.5.2=hd8ed1ab_1
  • cached_property=1.5.2=pyha770c72_1
  • cairo=1.18.0=h3faef2a_0
  • certifi=2024.7.4=pyhd8ed1ab_0
  • cffi=1.16.0=py38h6d47a40_0
  • charset-normalizer=3.3.2=pyhd3eb1b0_0
  • click=8.1.7=unix_pyh707e725_0
  • comm=0.2.2=pyhd8ed1ab_0
  • contourpy=1.0.5=py38hdb19cb5_0
  • cryptography=39.0.0=py38h1724139_0
  • cudatoolkit=11.0.221=h6bb024c_0
  • cudnn=8.0.0=cuda11.0_0
  • cycler=0.11.0=pyhd3eb1b0_0
  • cython=3.0.10=py38h5eee18b_0
  • dbus=1.13.18=hb2f20db_0
  • debugpy=1.8.2=py38h854fd01_0
  • decorator=5.1.1=pyhd8ed1ab_0
  • defusedxml=0.7.1=pyhd8ed1ab_0
  • entrypoints=0.4=pyhd8ed1ab_0
  • exceptiongroup=1.2.2=pyhd8ed1ab_0
  • executing=2.0.1=pyhd8ed1ab_0
  • expat=2.6.2=h6a678d5_0
  • font-ttf-dejavu-sans-mono=2.37=hd3eb1b0_0
  • font-ttf-inconsolata=2.001=hcb22688_0
  • font-ttf-source-code-pro=2.030=hd3eb1b0_0
  • font-ttf-ubuntu=0.83=h8b1ccd4_0
  • fontconfig=2.14.2=h14ed4e7_0
  • fonts-anaconda=1=h8fa9717_0
  • fonts-conda-ecosystem=1=hd3eb1b0_0
  • fonttools=4.51.0=py38h5eee18b_0
  • fqdn=1.5.1=pyhd8ed1ab_0
  • freetype=2.12.1=h4a9f257_0
  • frozenlist=1.4.1=py38h01eb140_0
  • gettext=0.22.5=h59595ed_2
  • gettext-tools=0.22.5=h59595ed_2
  • giflib=5.2.2=hd590300_0
  • glib=2.80.2=hf974151_0
  • glib-tools=2.80.2=hb6ce0ca_0
  • google-pasta=0.2.0=pyh8c360ce_0
  • graphite2=1.3.14=h295c915_1
  • grpc-cpp=1.36.4=hf89561c_1
  • gst-plugins-base=1.14.1=h6a678d5_1
  • gstreamer=1.14.1=h5eee18b_1
  • h11=0.14.0=pyhd8ed1ab_0
  • h2=4.1.0=pyhd8ed1ab_0
  • h5py=2.10.0=nompi_py38h9915d05_106
  • harfbuzz=8.5.0=hfac3d4d_0
  • hdf5=1.10.6=nompi_h6a2412b_1114
  • hpack=4.0.0=pyh9f0ad1d_0
  • httpcore=1.0.5=pyhd8ed1ab_0
  • httpx=0.27.0=pyhd8ed1ab_0
  • hyperframe=6.0.1=pyhd8ed1ab_0
  • icu=73.2=h59595ed_0
  • idna=3.7=py38h06a4308_0
  • importlib-metadata=8.2.0=pyha770c72_0
  • importlib_metadata=8.2.0=hd8ed1ab_0
  • importlib_resources=6.4.0=py38h06a4308_0
  • intervaltree=3.1.0=pyhd3eb1b0_0
  • ipykernel=6.29.5=pyh3099207_0
  • ipython=8.12.2=pyh41d4057_0
  • isoduration=20.11.0=pyhd8ed1ab_0
  • jedi=0.19.1=pyhd8ed1ab_0
  • jinja2=3.1.4=pyhd8ed1ab_0
  • joblib=1.4.2=py38h06a4308_0
  • jpeg=9e=h166bdaf_2
  • json5=0.9.25=pyhd8ed1ab_0
  • jsonpointer=3.0.0=py38h578d9bd_0
  • jsonschema=4.23.0=pyhd8ed1ab_0
  • jsonschema-specifications=2023.12.1=pyhd8ed1ab_0
  • jsonschema-with-format-nongpl=4.23.0=hd8ed1ab_0
  • jupyter-lsp=2.2.5=pyhd8ed1ab_0
  • jupyter_client=8.6.2=pyhd8ed1ab_0
  • jupyter_core=5.7.2=py38h578d9bd_0
  • jupyter_events=0.10.0=pyhd8ed1ab_0
  • jupyter_server=2.14.2=pyhd8ed1ab_0
  • jupyter_server_terminals=0.5.3=pyhd8ed1ab_0
  • jupyterlab=4.2.4=pyhd8ed1ab_0
  • jupyterlab_pygments=0.3.0=pyhd8ed1ab_1
  • jupyterlab_server=2.27.3=pyhd8ed1ab_0
  • keras-preprocessing=1.1.2=pyhd8ed1ab_0
  • keyutils=1.6.1=h166bdaf_0
  • kiwisolver=1.4.4=py38h6a678d5_0
  • krb5=1.20.1=hf9c8cef_0
  • lame=3.100=h7b6447c_0
  • lcms2=2.12=hddcbb42_0
  • ld_impl_linux-64=2.38=h1181459_1
  • lerc=4.0.0=h27087fc_0
  • libasprintf=0.22.5=h661eb56_2
  • libasprintf-devel=0.22.5=h661eb56_2
  • libbrotlicommon=1.0.9=h5eee18b_8
  • libbrotlidec=1.0.9=h5eee18b_8
  • libbrotlienc=1.0.9=h5eee18b_8
  • libcap=2.69=h0f662aa_0
  • libclang-cpp15=15.0.7=default_h127d8a8_5
  • libclang13=14.0.6=default_h9986a30_1
  • libcups=2.3.3=h36d4200_3
  • libcurl=7.88.1=h91b91d3_2
  • libdeflate=1.20=hd590300_0
  • libedit=3.1.20230828=h5eee18b_0
  • libev=4.33=h7f8727e_1
  • libevent=2.1.10=h9b69904_4
  • libexpat=2.6.2=h59595ed_0
  • libffi=3.4.4=h6a678d5_1
  • libflac=1.4.3=h59595ed_0
  • libgcc-ng=14.1.0=h77fa898_0
  • libgcrypt=1.11.0=h4ab18f5_1
  • libgettextpo=0.22.5=h59595ed_2
  • libgettextpo-devel=0.22.5=h59595ed_2
  • libgfortran-ng=11.2.0=h00389a5_1
  • libgfortran5=11.2.0=h1234567_1
  • libglib=2.80.2=hf974151_0
  • libgomp=14.1.0=h77fa898_0
  • libgpg-error=1.50=h4f305b6_0
  • libiconv=1.17=hd590300_2
  • libjpeg-turbo=2.1.4=h166bdaf_0
  • libllvm14=14.0.6=hcd5def8_4
  • libllvm15=15.0.7=hb3ce162_4
  • libllvm18=18.1.7=hb77312f_0
  • libnghttp2=1.52.0=ha637b67_1
  • libnsl=2.0.1=hd590300_0
  • libogg=1.3.5=h27cfd23_1
  • libopenblas=0.3.21=h043d6bf_0
  • libopus=1.3.1=h7b6447c_0
  • libpng=1.6.43=h2797004_0
  • libpq=12.15=h37d81fd_1
  • libprotobuf=3.15.8=h780b84a_1
  • libsndfile=1.2.2=hc60ed4a_1
  • libsodium=1.0.18=h36c2ea0_1
  • libsqlite=3.46.0=hde9e2c9_0
  • libssh2=1.10.0=haa6b8db_3
  • libstdcxx-ng=14.1.0=hc0a3c3a_0
  • libsystemd0=255=h3516f8a_1
  • libtiff=4.2.0=hf544144_3
  • libuuid=2.38.1=h0b41bf4_0
  • libvorbis=1.3.7=h7b6447c_0
  • libwebp-base=1.3.2=h5eee18b_0
  • libxcb=1.15=h7f8727e_0
  • libxkbcommon=1.7.0=h662e7e4_0
  • libxml2=2.12.7=hc051c1a_1
  • libzlib=1.2.13=h4ab18f5_6
  • lz4-c=1.9.4=h6a678d5_1
  • markdown=3.6=pyhd8ed1ab_0
  • markupsafe=2.1.5=py38h01eb140_0
  • matplotlib=3.7.2=py38h06a4308_0
  • matplotlib-base=3.7.2=py38h1128e8f_0
  • matplotlib-inline=0.1.7=pyhd8ed1ab_0
  • mistune=3.0.2=pyhd8ed1ab_0
  • mpg123=1.32.6=h59595ed_0
  • multidict=6.0.5=py38h01eb140_0
  • mysql=5.7.20=hf484d3e_1001
  • mysql-common=8.0.32=h14678bc_0
  • mysql-libs=8.0.32=h54cf53e_0
  • natsort=7.1.1=pyhd3eb1b0_0
  • nbclient=0.10.0=pyhd8ed1ab_0
  • nbconvert-core=7.16.4=pyhd8ed1ab_1
  • nbformat=5.10.4=pyhd8ed1ab_0
  • ncurses=6.4=h6a678d5_0
  • nest-asyncio=1.6.0=pyhd8ed1ab_0
  • networkx=3.1=py38h06a4308_0
  • notebook-shim=0.2.4=pyhd8ed1ab_0
  • nspr=4.35=h6a678d5_0
  • nss=3.100=hca3bf56_0
  • numexpr=2.8.4=py38hd2a5715_1
  • oauthlib=3.2.2=pyhd8ed1ab_0
  • olefile=0.47=pyhd8ed1ab_0
  • openjpeg=2.4.0=hb52868f_1
  • openssl=1.1.1w=hd590300_0
  • opt_einsum=3.3.0=pyhc1e730c_2
  • overrides=7.7.0=pyhd8ed1ab_0
  • packaging=24.1=py38h06a4308_0
  • pandas=2.0.3=py38h1128e8f_0
  • pandocfilters=1.5.0=pyhd8ed1ab_0
  • parso=0.8.4=pyhd8ed1ab_0
  • patsy=0.5.6=py38h06a4308_0
  • pcre2=10.43=hcad00b1_0
  • pexpect=4.9.0=pyhd8ed1ab_0
  • pickleshare=0.7.5=py_1003
  • pillow=8.2.0=py38ha0e1e83_1
  • pip=24.0=py38h06a4308_0
  • pixman=0.43.2=h59595ed_0
  • pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1
  • platformdirs=3.10.0=py38h06a4308_0
  • ply=3.11=py38_0
  • pooch=1.7.0=py38h06a4308_0
  • prometheus_client=0.20.0=pyhd8ed1ab_0
  • prompt-toolkit=3.0.47=pyha770c72_0
  • prompt_toolkit=3.0.47=hd8ed1ab_0
  • psutil=6.0.0=py38hfb59056_0
  • ptyprocess=0.7.0=pyhd3deb0d_0
  • pulseaudio-client=17.0=hb77b528_0
  • pure_eval=0.2.3=pyhd8ed1ab_0
  • pyasn1=0.6.0=pyhd8ed1ab_0
  • pyasn1-modules=0.4.0=pyhd8ed1ab_0
  • pybedtools=0.10.0=py38hd638cd3_2
  • pybigwig=0.3.22=py38hf8a4f86_0
  • pycparser=2.22=pyhd8ed1ab_0
  • pyerfa=2.0.0=py38h27cfd23_0
  • pygments=2.18.0=pyhd8ed1ab_0
  • pyjwt=2.8.0=pyhd8ed1ab_1
  • pyopenssl=23.2.0=pyhd8ed1ab_1
  • pyparsing=3.0.9=py38h06a4308_0
  • pyqt=5.15.10=py38h6a678d5_0
  • pyqt5-sip=12.13.0=py38h5eee18b_0
  • pysam=0.21.0=py38h1c8baaf_0
  • pysocks=1.7.1=py38h06a4308_0
  • python=3.8.15=h257c98d_0_cpython
  • python-dateutil=2.9.0post0=py38h06a4308_2
  • python-fastjsonschema=2.20.0=pyhd8ed1ab_0
  • python-flatbuffers=1.12=pyhd8ed1ab_1
  • python-json-logger=2.0.7=pyhd8ed1ab_0
  • python-tzdata=2023.3=pyhd3eb1b0_0
  • python_abi=3.8=2_cp38
  • pytz=2024.1=py38h06a4308_0
  • pyu2f=0.1.5=pyhd8ed1ab_0
  • pyyaml=6.0.1=py38h5eee18b_0
  • pyzmq=26.0.3=py38ha44f8e3_0
  • qt-main=5.15.2=h110a718_10
  • re2=2021.04.01=h9c3ff4c_0
  • readline=8.2=h5eee18b_0
  • referencing=0.35.1=pyhd8ed1ab_0
  • requests=2.32.3=py38h06a4308_0
  • requests-oauthlib=2.0.0=pyhd8ed1ab_0
  • rfc3339-validator=0.1.4=pyhd8ed1ab_0
  • rfc3986-validator=0.1.1=pyh9f0ad1d_0
  • rpds-py=0.19.1=py38h4005ec7_0
  • rsa=4.9=pyhd8ed1ab_0
  • scikit-learn=1.3.0=py38h1128e8f_1
  • scipy=1.10.1=py38h32ae08f_1
  • seaborn=0.13.2=py38h06a4308_0
  • send2trash=1.8.3=pyh0d859eb_0
  • setuptools=69.5.1=py38h06a4308_0
  • sip=6.7.12=py38h6a678d5_0
  • six=1.16.0=pyhd3eb1b0_1
  • snappy=1.1.10=hdb0a2a9_1
  • sniffio=1.3.1=pyhd8ed1ab_0
  • sortedcontainers=2.4.0=pyhd3eb1b0_0
  • soupsieve=2.5=pyhd8ed1ab_1
  • sqlite=3.45.3=h5eee18b_0
  • stack_data=0.6.2=pyhd8ed1ab_0
  • statsmodels=0.14.0=py38ha9d4c09_0
  • tabulate=0.9.0=py38h06a4308_0
  • tensorboard-plugin-wit=1.8.1=pyhd8ed1ab_0
  • tensorflow-base=2.4.0=py38h01d9eeb_0
  • termcolor=2.4.0=pyhd8ed1ab_0
  • terminado=0.18.1=pyh0d859eb_0
  • threadpoolctl=3.5.0=py38h2f386ee_0
  • tinycss2=1.3.0=pyhd8ed1ab_0
  • tk=8.6.14=h39e8969_0
  • tomli=2.0.1=py38h06a4308_0
  • tornado=6.4.1=py38h5eee18b_0
  • traitlets=5.14.3=pyhd8ed1ab_0
  • types-python-dateutil=2.9.0.20240316=pyhd8ed1ab_0
  • typing_extensions=4.12.2=pyha770c72_0
  • typing_utils=0.1.0=pyhd8ed1ab_0
  • unicodedata2=15.1.0=py38h5eee18b_0
  • uri-template=1.3.0=pyhd8ed1ab_0
  • urllib3=2.2.2=py38h06a4308_0
  • wcwidth=0.2.13=pyhd8ed1ab_0
  • webcolors=24.6.0=pyhd8ed1ab_0
  • webencodings=0.5.1=pyhd8ed1ab_2
  • websocket-client=1.8.0=pyhd8ed1ab_0
  • werkzeug=3.0.3=pyhd8ed1ab_0
  • wheel=0.43.0=py38h06a4308_0
  • wrapt=1.16.0=py38h01eb140_0
  • xcb-util=0.4.0=hd590300_1
  • xcb-util-image=0.4.0=h8ee46fc_1
  • xcb-util-keysyms=0.4.0=h8ee46fc_1
  • xcb-util-renderutil=0.3.9=hd590300_1
  • xcb-util-wm=0.4.1=h8ee46fc_1
  • xkeyboard-config=2.42=h4ab18f5_0
  • xorg-kbproto=1.0.7=h7f98852_1002
  • xorg-libice=1.1.1=hd590300_0
  • xorg-libsm=1.2.4=h7391055_0
  • xorg-libx11=1.8.9=h8ee46fc_0
  • xorg-libxau=1.0.11=hd590300_0
  • xorg-libxext=1.3.4=h0b41bf4_2
  • xorg-libxrender=0.9.11=hd590300_0
  • xorg-renderproto=0.11.1=h7f98852_1002
  • xorg-xextproto=7.3.0=h0b41bf4_1003
  • xorg-xf86vidmodeproto=2.3.1=h7f98852_1002
  • xorg-xproto=7.0.31=h27cfd23_1007
  • xz=5.2.6=h166bdaf_0
  • yaml=0.2.5=h7b6447c_0
  • yarl=1.9.4=py38h01eb140_0
  • zeromq=4.3.5=h59595ed_1
  • zipp=3.17.0=py38h06a4308_0
  • zlib=1.2.13=h4ab18f5_6
  • zstd=1.5.6=ha6fb4c9_0
  • pip:
    • asciitree==0.3.3
    • bioframe==0.7.2
    • cachetools==5.4.0
    • cooler==0.10.2
    • cooltools==0.7.1
    • cytoolz==0.12.3
    • dill==0.3.8
    • flatbuffers==24.3.25
    • gast==0.4.0
    • google-auth==2.32.0
    • google-auth-oauthlib==1.0.0
    • grpcio==1.65.1
    • imageio==2.34.2
    • keras==2.13.1
    • lazy-loader==0.4
    • libclang==18.1.1
    • llvmlite==0.41.1
    • multiprocess==0.70.16
    • numba==0.58.1
    • numpy==1.21.5
    • protobuf==4.25.4
    • pyfaidx==0.8.1.1
    • pywavelets==1.4.1
    • scikit-image==0.21.0
    • simplejson==3.19.2
    • tensorboard==2.13.0
    • tensorboard-data-server==0.7.2
    • tensorflow==2.13.1
    • tensorflow-estimator==2.13.0
    • tensorflow-io-gcs-filesystem==0.34.0
    • tifffile==2023.7.10
    • toolz==0.12.1
    • typing-extensions==4.5.0
      prefix: user/bin/.conda/akita
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