Adding model, graphs and metadata.
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- README.md +45 -0
- config.json +161 -0
- eval/eval_results.json +8 -0
- eval/sparsity_report.json +1 -0
- model_card/density_info.js +174 -0
- model_card/images/model_decoder_layers_0_encoder_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_0_encoder_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_0_encoder_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_0_encoder_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_0_fc1.png +0 -0
- model_card/images/model_decoder_layers_0_fc2.png +0 -0
- model_card/images/model_decoder_layers_0_self_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_0_self_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_0_self_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_0_self_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_1_encoder_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_1_encoder_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_1_encoder_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_1_encoder_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_1_fc1.png +0 -0
- model_card/images/model_decoder_layers_1_fc2.png +0 -0
- model_card/images/model_decoder_layers_1_self_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_1_self_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_1_self_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_1_self_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_2_encoder_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_2_encoder_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_2_encoder_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_2_encoder_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_2_fc1.png +0 -0
- model_card/images/model_decoder_layers_2_fc2.png +0 -0
- model_card/images/model_decoder_layers_2_self_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_2_self_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_2_self_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_2_self_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_3_encoder_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_3_encoder_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_3_encoder_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_3_encoder_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_3_fc1.png +0 -0
- model_card/images/model_decoder_layers_3_fc2.png +0 -0
- model_card/images/model_decoder_layers_3_self_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_3_self_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_3_self_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_3_self_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_4_encoder_attn_k_proj.png +0 -0
- model_card/images/model_decoder_layers_4_encoder_attn_out_proj.png +0 -0
- model_card/images/model_decoder_layers_4_encoder_attn_q_proj.png +0 -0
- model_card/images/model_decoder_layers_4_encoder_attn_v_proj.png +0 -0
- model_card/images/model_decoder_layers_4_fc1.png +0 -0
README.md
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---
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language: en
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license: apache-2.0
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tags:
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- summarization
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datasets:
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- cnn_dailymail
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metrics:
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- R1
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- R2
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- RL
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---
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## facebook/bart-base model fine-tuned on CNN/DailyMail
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This model was created using the [nn_pruning](https://github.com/huggingface/nn_pruning) python library: the linear layers contains **23%** of the original weights.
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The model contains **45%** of the original weights **overall** (the embeddings account for a significant part of the model, and they are not pruned by this method).
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<div class="graph"><script src="/echarlaix/bart-base-cnn-r2-18.7-d23-hybrid/raw/main/model_card/density_info.js" id="4348cd46-05bd-4e27-b565-6693f9e0b03e"></script></div>
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## Fine-Pruning details
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This model was fine-tuned from the HuggingFace [model](https://huggingface.co/facebook/bart-base).
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A side-effect of block pruning is that some of the attention heads are completely removed: 61 heads were removed on a total of 216 (28.2%).
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<div class="graph"><script src="/echarlaix/bart-base-cnn-r2-18.7-d23-hybrid/raw/main/model_card/pruning_info.js" id="733e6c04-6c58-482f-89b8-a196de6b6550"></script></div>
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## Details of the CNN/DailyMail dataset
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| Dataset | Split | # samples |
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| ------------- | ----- | --------- |
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| CNN/DailyMail | train | 287K |
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| CNN/DailyMail | eval | 13K |
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### Results
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| Metric | # Value |
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| ----------- | --------- |
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| **Rouge 1** | **41.43** |
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| **Rouge 2** | **18.72** |
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| **Rouge L** | **38.35** |
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config.json
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{
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"_name_or_path": "/tmp/tmpdmtb8m2s",
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"activation_dropout": 0.1,
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"activation_function": "gelu",
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"add_bias_logits": false,
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"add_final_layer_norm": false,
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"architectures": [
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"BartForConditionalGeneration"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 0,
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"classif_dropout": 0.1,
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"classifier_dropout": 0.0,
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"d_model": 768,
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"decoder_attention_heads": 12,
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"decoder_ffn_dim": 3072,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 6,
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"decoder_start_token_id": 2,
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"dropout": 0.1,
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"early_stopping": true,
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"encoder_attention_heads": 12,
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"encoder_ffn_dim": 3072,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 6,
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"eos_token_id": 2,
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"forced_eos_token_id": 2,
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"gradient_checkpointing": false,
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"heads_count": 216,
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"heads_to_prune": {
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"0": [
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],
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"1": [
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],
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"10": [
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],
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"11": [
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],
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"2": [
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],
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"3": [
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],
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"4": [
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],
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"5": [
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],
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"6": [
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],
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"7": [
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],
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"8": [
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],
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"9": [
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]
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},
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"init_std": 0.02,
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"is_encoder_decoder": true,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"max_position_embeddings": 1024,
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"model_type": "bart",
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"no_repeat_ngram_size": 3,
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"normalize_before": false,
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"normalize_embedding": true,
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"num_beams": 4,
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"num_hidden_layers": 6,
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"pad_token_id": 1,
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"scale_embedding": false,
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"task_specific_params": {
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"summarization": {
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"length_penalty": 1.0,
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"max_length": 128,
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"min_length": 12,
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"num_beams": 4
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},
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"summarization_cnn": {
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"length_penalty": 2.0,
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"max_length": 142,
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"min_length": 56,
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"num_beams": 4
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},
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"summarization_xsum": {
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"length_penalty": 1.0,
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"max_length": 62,
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"min_length": 11,
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"num_beams": 6
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}
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},
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"transformers_version": "4.4.1",
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"use_cache": true,
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"vocab_size": 50265
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}
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eval/eval_results.json
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{
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"eval_gen_len": 81.1528,
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"eval_loss": 2.02736759185791,
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"eval_rouge1": 41.4282,
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"eval_rouge2": 18.7209,
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"eval_rougeL": 28.2805,
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"eval_rougeLsum": 38.3536
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}
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eval/sparsity_report.json
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{"total": 139420416, "nnz": 63361439, "linear_total": 99090432, "linear_nnz": 23081472, "layers": {"0": {"total": 16539648, "nnz": 4338402, "linear_total": 16515072, "linear_nnz": 4321280, "linear_attention_total": 7077888, "linear_attention_nnz": 4170752, "linear_dense_total": 9437184, "linear_dense_nnz": 150528}, "1": {"total": 16539648, "nnz": 3697201, "linear_total": 16515072, "linear_nnz": 3680768, "linear_attention_total": 7077888, "linear_attention_nnz": 3261440, "linear_dense_total": 9437184, "linear_dense_nnz": 419328}, "2": {"total": 16539648, "nnz": 3582655, "linear_total": 16515072, "linear_nnz": 3566080, "linear_attention_total": 7077888, "linear_attention_nnz": 3076096, "linear_dense_total": 9437184, "linear_dense_nnz": 489984}, "3": {"total": 16539648, "nnz": 3230637, "linear_total": 16515072, "linear_nnz": 3214848, "linear_attention_total": 7077888, "linear_attention_nnz": 2703360, "linear_dense_total": 9437184, "linear_dense_nnz": 511488}, "4": {"total": 16539648, "nnz": 3432491, "linear_total": 16515072, "linear_nnz": 3416576, "linear_attention_total": 7077888, "linear_attention_nnz": 3104768, "linear_dense_total": 9437184, "linear_dense_nnz": 311808}, "5": {"total": 16539648, "nnz": 4899061, "linear_total": 16515072, "linear_nnz": 4881920, "linear_attention_total": 7077888, "linear_attention_nnz": 4456448, "linear_dense_total": 9437184, "linear_dense_nnz": 425472}}, "total_sparsity": 54.55368674269341, "linear_sparsity": 76.70665922619048, "pruned_heads": {"0": [8, 10], "1": [0, 5, 6], "2": [4, 6, 9], "3": [0, 1, 2, 4, 6, 7, 8, 9, 11], "4": [1, 2, 5, 6, 9, 10, 11], "5": [2, 3, 4, 5, 6, 10], "6": [0, 12, 13, 14], "7": [2, 11, 16, 17, 18, 19, 23], "8": [2, 14, 16, 21], "9": [3, 12, 13, 15, 16, 18, 21, 22], "10": [3, 12, 14, 16, 18, 20, 21], "11": [10]}}
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model_card/density_info.js
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|
1 |
+
(function() {
|
2 |
+
var fn = function() {
|
3 |
+
|
4 |
+
(function(root) {
|
5 |
+
function now() {
|
6 |
+
return new Date();
|
7 |
+
}
|
8 |
+
|
9 |
+
var force = false;
|
10 |
+
|
11 |
+
if (typeof root._bokeh_onload_callbacks === "undefined" || force === true) {
|
12 |
+
root._bokeh_onload_callbacks = [];
|
13 |
+
root._bokeh_is_loading = undefined;
|
14 |
+
}
|
15 |
+
|
16 |
+
|
17 |
+
|
18 |
+
|
19 |
+
var element = document.getElementById("4348cd46-05bd-4e27-b565-6693f9e0b03e");
|
20 |
+
if (element == null) {
|
21 |
+
console.warn("Bokeh: autoload.js configured with elementid '4348cd46-05bd-4e27-b565-6693f9e0b03e' but no matching script tag was found.")
|
22 |
+
}
|
23 |
+
|
24 |
+
|
25 |
+
function run_callbacks() {
|
26 |
+
try {
|
27 |
+
root._bokeh_onload_callbacks.forEach(function(callback) {
|
28 |
+
if (callback != null)
|
29 |
+
callback();
|
30 |
+
});
|
31 |
+
} finally {
|
32 |
+
delete root._bokeh_onload_callbacks
|
33 |
+
}
|
34 |
+
console.debug("Bokeh: all callbacks have finished");
|
35 |
+
}
|
36 |
+
|
37 |
+
function load_libs(css_urls, js_urls, callback) {
|
38 |
+
if (css_urls == null) css_urls = [];
|
39 |
+
if (js_urls == null) js_urls = [];
|
40 |
+
|
41 |
+
root._bokeh_onload_callbacks.push(callback);
|
42 |
+
if (root._bokeh_is_loading > 0) {
|
43 |
+
console.debug("Bokeh: BokehJS is being loaded, scheduling callback at", now());
|
44 |
+
return null;
|
45 |
+
}
|
46 |
+
if (js_urls == null || js_urls.length === 0) {
|
47 |
+
run_callbacks();
|
48 |
+
return null;
|
49 |
+
}
|
50 |
+
console.debug("Bokeh: BokehJS not loaded, scheduling load and callback at", now());
|
51 |
+
root._bokeh_is_loading = css_urls.length + js_urls.length;
|
52 |
+
|
53 |
+
function on_load() {
|
54 |
+
root._bokeh_is_loading--;
|
55 |
+
if (root._bokeh_is_loading === 0) {
|
56 |
+
console.debug("Bokeh: all BokehJS libraries/stylesheets loaded");
|
57 |
+
run_callbacks()
|
58 |
+
}
|
59 |
+
}
|
60 |
+
|
61 |
+
function on_error(url) {
|
62 |
+
console.error("failed to load " + url);
|
63 |
+
}
|
64 |
+
|
65 |
+
for (let i = 0; i < css_urls.length; i++) {
|
66 |
+
const url = css_urls[i];
|
67 |
+
const element = document.createElement("link");
|
68 |
+
element.onload = on_load;
|
69 |
+
element.onerror = on_error.bind(null, url);
|
70 |
+
element.rel = "stylesheet";
|
71 |
+
element.type = "text/css";
|
72 |
+
element.href = url;
|
73 |
+
console.debug("Bokeh: injecting link tag for BokehJS stylesheet: ", url);
|
74 |
+
document.body.appendChild(element);
|
75 |
+
}
|
76 |
+
|
77 |
+
const hashes = {"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js": "XypntL49z55iwGVUW4qsEu83zKL3XEcz0MjuGOQ9SlaaQ68X/g+k1FcioZi7oQAc", "https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js": "bEsM86IHGDTLCS0Zod8a8WM6Y4+lafAL/eSiyQcuPzinmWNgNO2/olUF0Z2Dkn5i", "https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js": "TX0gSQTdXTTeScqxj6PVQxTiRW8DOoGVwinyi1D3kxv7wuxQ02XkOxv0xwiypcAH"};
|
78 |
+
|
79 |
+
for (let i = 0; i < js_urls.length; i++) {
|
80 |
+
const url = js_urls[i];
|
81 |
+
const element = document.createElement('script');
|
82 |
+
element.onload = on_load;
|
83 |
+
element.onerror = on_error.bind(null, url);
|
84 |
+
element.async = false;
|
85 |
+
element.src = url;
|
86 |
+
if (url in hashes) {
|
87 |
+
element.crossOrigin = "anonymous";
|
88 |
+
element.integrity = "sha384-" + hashes[url];
|
89 |
+
}
|
90 |
+
console.debug("Bokeh: injecting script tag for BokehJS library: ", url);
|
91 |
+
document.head.appendChild(element);
|
92 |
+
}
|
93 |
+
};
|
94 |
+
|
95 |
+
function inject_raw_css(css) {
|
96 |
+
const element = document.createElement("style");
|
97 |
+
element.appendChild(document.createTextNode(css));
|
98 |
+
document.body.appendChild(element);
|
99 |
+
}
|
100 |
+
|
101 |
+
|
102 |
+
var js_urls = ["https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js", "https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js", "https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js"];
|
103 |
+
var css_urls = [];
|
104 |
+
|
105 |
+
|
106 |
+
var inline_js = [
|
107 |
+
function(Bokeh) {
|
108 |
+
Bokeh.set_log_level("info");
|
109 |
+
},
|
110 |
+
|
111 |
+
function(Bokeh) {
|
112 |
+
(function() {
|
113 |
+
var fn = function() {
|
114 |
+
Bokeh.safely(function() {
|
115 |
+
(function(root) {
|
116 |
+
function embed_document(root) {
|
117 |
+
|
118 |
+
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