[KV Cache Interface] Text Generation & Decoder Engine Implementation #1089

dbogunowicz · 2023-06-22T07:08:29Z

Testing plan:

No-cache inference

from deepsparse import Pipeline
import time
start = time.time()
opt = Pipeline.create(task="opt",
                      model_path="/home/ubuntu/damian/sparseml/deployment",
                      engine_type = "onnxruntime",
                      max_generated_tokens=1)
prompt = "Who is the president of the United States?"
output = opt(sequences=prompt, return_logits=True)

sequences=['\n'] logits=array([[[-12.644863 , -12.9746065,   2.577626 , ..., -13.5366125,
         -13.376596 , -14.587112 ]]], dtype=float32) session_id=None # same as in pytorch inference

Ground truth: [-12.6449, -12.9746,   2.5776,  ..., -13.5366, -13.3766, -14.5871]

Single-token engine decoding only:

from deepsparse import Pipeline
opt = Pipeline.create(task="opt",
                      model_path="/home/ubuntu/damian/sparseml/deployment",
                      engine_type = "onnxruntime",
                      max_generated_tokens=128)
prompt = "Who is the president of the United States?"
output = opt(sequences=prompt)
print(output.sequences)

2023-06-27 07:55:20 deepsparse.transformers.engines.nl_decoder_engine INFO     Overwriting in-place the input shapes of the transformer model at /home/ubuntu/damian/sparseml/deployment/model.onnx
2023-06-27 07:55:24 deepsparse.utils.onnx INFO     Overwriting in-place the batch size of the model at /home/ubuntu/damian/sparseml/deployment/model.onnx
2023-06-27 07:56:37 deepsparse.transformers.engines.nl_decoder_engine INFO     Overwriting in-place the input shapes of the transformer model at /home/ubuntu/damian/sparseml/deployment/model.onnx
2023-06-27 07:56:40 deepsparse.utils.onnx INFO     Overwriting in-place the batch size of the model at /home/ubuntu/damian/sparseml/deployment/model.onnx
['\n\nThe president of the United States is the head of the executive branch of government. The president is the head of the executive branch of government, and the president is the head of the executive branch of government. The president is the head of the executive branch of government, and the president is the head of the executive branch of government.\n\nThe president is the head of the executive branch of government, and the president is the head of the executive branch of government. The president is the head of the executive branch of government, and the president is the head of the executive branch of government. The president is the head of the executive']

Ground truth: The president of the United States is the head of the executive branch of government. The president is the head of the executive branch of government, and the president is the head of the executive branch of government. The president is the head of the executive branch of government, and the president is the head of the executive branch of government.

The president is the head of the executive branch of government, and the president is the head of the executive branch of government. The president is the head of the executive branch of government, and the president is the head of the executive branch of government.

Single-token engine and multi-token engine decoding:

from deepsparse import Pipeline
opt = Pipeline.create(task="opt",
                      model_path="/home/ubuntu/damian/sparseml/deployment",
                      engine_type = "onnxruntime",
                      max_generated_tokens=128)
prompt = "Who is the president of the United States?" * 20
output = opt(sequences=prompt)
print(output.sequences)

2023-06-27 07:57:53 deepsparse.transformers.engines.nl_decoder_engine INFO     Overwriting in-place the input shapes of the transformer model at /home/ubuntu/damian/sparseml/deployment/model.onnx
2023-06-27 07:58:47 deepsparse.utils.onnx INFO     Overwriting in-place the batch size of the model at /home/ubuntu/damian/sparseml/deployment/model.onnx
2023-06-27 07:58:52 deepsparse.transformers.engines.nl_decoder_engine INFO     Overwriting in-place the input shapes of the transformer model at /home/ubuntu/damian/sparseml/deployment/model.onnx
2023-06-27 07:58:58 deepsparse.utils.onnx INFO     Overwriting in-place the batch size of the model at /home/ubuntu/damian/sparseml/deployment/model.onnx
['Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is']

Ground truth: Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?Who is the president of the United States?

* initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate

* initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate * initial commit * change order * Update examples/codegen/README.md Co-authored-by: corey-nm <[email protected]> --------- Co-authored-by: corey-nm <[email protected]>

… window not yet implemented!

…esult. Hey, this is good news still

…E: tokens past the base seq len are repeated

…nizer

…in the wrong place

src/deepsparse/transformers/pipelines/text_generation.py

…e_ort

…o feature/damian/decoder_engine

…e_ort

…r_engine

bfineran

Looks great overall very clean implementation - see comments. I'm most concerned about how we only allow an engine to contain a single cache and single session. this will not scale. the design looks simple enough that we should probably just expand do basic multiple session support now (use dict as suggested in comment, etc).

additionally let's see what we can do in terms of testing

src/deepsparse/transformers/engines/nl_decoder_engine.py

bfineran · 2023-06-27T20:46:36Z

src/deepsparse/transformers/engines/nl_decoder_engine.py

+        :param engine: The `NLDecoderEngine` to transfer the kv cache state
+            from
+        """
+        state = engine.kv_cache.cached_inputs


let's have this function take the engine KVCache directly (again this is because we will have multiple cache objects per engine once we're in multi session/multi stream)

Ok, but this only works nicely if KVCache tracks the amount of cache that it has processed.

Agreement: each KVCache session tracks the number of processed tokens

bfineran · 2023-06-27T20:47:54Z

src/deepsparse/transformers/pipelines/text_generation.py

+            use_deepsparse_cache=use_deepsparse_cache,
+        )
+
+        if self.multitoken_engine.kv_cache_enabled:


it seems like we're using KV cache enabled as a proxy for if we want to generate multiple tokens or not, no? seems like we might want to make this a separate, explicit control

src/deepsparse/transformers/pipelines/text_generation.py

bfineran · 2023-06-27T20:49:01Z

src/deepsparse/transformers/pipelines/text_generation.py

+            sequence of generated tokens and a sequence
+            of logits for each generated token
+        """
+        if not self.multitoken_engine.kv_cache_enabled:


same here, we should be just use max generated tokens

if not self.multitoken_engine.kv_cache_enabled and self.max_generated_tokens != 1: error

* initial commit * Update src/deepsparse/license.py * limit to 150mb * ready to review * initial commit * [Codegen][ORT][Static Seq Length] TextGenerationPipeline (#946) * initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate * [CodeGen][Documentation] (#956) * initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate * initial commit * change order * Update examples/codegen/README.md Co-authored-by: corey-nm <[email protected]> --------- Co-authored-by: corey-nm <[email protected]> * reimplementation for generative pipelines * restore text generation from examples * [CodeGen] ONNX model loading to support >2Gb models / two engines (#991) * refactor sucessfull * Pipeline fully refactored, time to test engine support. Note: Sliding window not yet implemented! * First iteration with Sage * Apply suggestions from code review * ORT agrees with the Engine. But they both give not entirely correct result. Hey, this is good news still * dynamic ORT vs static DS * pipeline handles OPT multitoken pass * fixes to get static pipeline a little further along * adjust shapes and slicing to enable static autoregressive pass - ISSUE: tokens past the base seq len are repeated * migrate from cache_length to positions input * got if working for multitoken + single token scenario * cleanup the pipeline * further cleanup post merge * Pipeline working for single-token inference only * do not load the onnx model with external files twice * pipeline never redundantly saves the external data + more robust tokenizer * Stop saving tmp files, otherwise the engine looks for external files in the wrong place * Left pad support * cleanup * cleanup2 * Add in pipeline timing * add in force tokens logic * remove input validation for text generation pipelines * remove multitoken support for now * remove kv cache engine and other fixes * nest input shape override * comment out input shape override * add non batch override for ORT * clean up generation pipeline * initial commit * Update src/deepsparse/license.py * limit to 150mb * ready to review * fix the erronous Makefile * perhaps fixed GHA * take into consideration that GHA creates four files * initial commit * tested with actual model * remove val_inp argument * Update README.md * Apply suggestions from code review * Update README.md * [BugFix] Update deepsparse dockerfile (#1069) * Remove autoinstall triggering commands * Fix typo * initial implementation * working implementation for pipeline input * [Fix] Fix CLI benchmark errors (#1071) * initial commit * ready for review * Update src/deepsparse/utils/onnx.py * Clean a typo in the pipeline code * initial commit * [KV Cache Interface] DecoderKVCache (#1084) * initial implementation * initial implementation * Revert "initial implementation" This reverts commit 765a5f7. * Merge DecoderKVCache with KVCacheORT (KVCacheORT will not exist, it is just an abstraction) * rebase * add tests * DecoderKVCache that manipulates cache state and additionally passes info to the engine via KVCache object * improvements after the sync with Mark * remove prefill * fix the computation of total cache capacity * address PR comments * [WiP] [KV Cache Interface] Text Generation & Decoder Engine Implementation (#1089) * initial commit * Update src/deepsparse/license.py * limit to 150mb * ready to review * initial commit * [Codegen][ORT][Static Seq Length] TextGenerationPipeline (#946) * initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate * [CodeGen][Documentation] (#956) * initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate * initial commit * change order * Update examples/codegen/README.md Co-authored-by: corey-nm <[email protected]> --------- Co-authored-by: corey-nm <[email protected]> * reimplementation for generative pipelines * restore text generation from examples * [CodeGen] ONNX model loading to support >2Gb models / two engines (#991) * refactor sucessfull * Pipeline fully refactored, time to test engine support. Note: Sliding window not yet implemented! * First iteration with Sage * Apply suggestions from code review * ORT agrees with the Engine. But they both give not entirely correct result. Hey, this is good news still * dynamic ORT vs static DS * pipeline handles OPT multitoken pass * fixes to get static pipeline a little further along * adjust shapes and slicing to enable static autoregressive pass - ISSUE: tokens past the base seq len are repeated * migrate from cache_length to positions input * got if working for multitoken + single token scenario * cleanup the pipeline * further cleanup post merge * Pipeline working for single-token inference only * do not load the onnx model with external files twice * pipeline never redundantly saves the external data + more robust tokenizer * Stop saving tmp files, otherwise the engine looks for external files in the wrong place * Left pad support * cleanup * cleanup2 * Add in pipeline timing * add in force tokens logic * remove input validation for text generation pipelines * remove multitoken support for now * remove kv cache engine and other fixes * nest input shape override * comment out input shape override * add non batch override for ORT * clean up generation pipeline * initial commit * Update src/deepsparse/license.py * limit to 150mb * ready to review * fix the erronous Makefile * perhaps fixed GHA * take into consideration that GHA creates four files * initial commit * tested with actual model * remove val_inp argument * Update README.md * Apply suggestions from code review * Update README.md * initial implementation * initial implementation * Revert "initial implementation" This reverts commit 765a5f7. * rebase * add tests * strip down complexity out of text generation pipeline * initial implementation * In a good state for the review on 22.06 * remove files to make review easier * Revert "remove files to make review easier" This reverts commit ea82e99. * Merge DecoderKVCache with KVCacheORT (KVCacheORT will not exist, it is just an abstraction) * rebase * add tests * Delete decoder_kv_cache.py * Delete test_decoder_kv_cache.py * DecoderKVCache that manipulates cache state and additionally passes info to the engine via KVCache object * fix formatting of the transformers/utils/__init__.py * improvements after the sync with Mark * All changes applied, time for testing * Scaffolding to also run multitoken * add delay_overwriting_inputs * multitoken is working (although in limited capacity) * fix no kv cache inference * Do not create engine if not needed * remove the prefill option * fix docstring * remove prefill * fix the computation of total cache capacity * merge * addressed PR comments * quality --------- Co-authored-by: corey-nm <[email protected]> Co-authored-by: Mark Kurtz <[email protected]> Co-authored-by: Benjamin <[email protected]> * now kv cache decoder holds information about the num of tokens preprocessed. also encountered first bug when running with the engine * cleanup the old files * Update src/deepsparse/transformers/engines/nl_decoder_engine.py * ready for review * ready for testing * managed to get first logits right * Delete example * cleanup before sharing with Ben and Sage * Update src/deepsparse/transformers/engines/nl_decoder_engine.py * assert proper padding on pipeline init * now also supporting kv cache perplexity. time for cleanup * ready for review * correctly print engine info * work with left padding of the tokenizer * quality * fix the multitoken inference * Perplexity Eval for Text Generation Models (#1073) * initial commit * Update src/deepsparse/license.py * limit to 150mb * ready to review * initial commit * [Codegen][ORT][Static Seq Length] TextGenerationPipeline (#946) * initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate * [CodeGen][Documentation] (#956) * initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate * initial commit * change order * Update examples/codegen/README.md Co-authored-by: corey-nm <[email protected]> --------- Co-authored-by: corey-nm <[email protected]> * reimplementation for generative pipelines * restore text generation from examples * [CodeGen] ONNX model loading to support >2Gb models / two engines (#991) * refactor sucessfull * Pipeline fully refactored, time to test engine support. Note: Sliding window not yet implemented! * First iteration with Sage * Apply suggestions from code review * ORT agrees with the Engine. But they both give not entirely correct result. Hey, this is good news still * dynamic ORT vs static DS * pipeline handles OPT multitoken pass * fixes to get static pipeline a little further along * adjust shapes and slicing to enable static autoregressive pass - ISSUE: tokens past the base seq len are repeated * migrate from cache_length to positions input * got if working for multitoken + single token scenario * cleanup the pipeline * further cleanup post merge * Pipeline working for single-token inference only * do not load the onnx model with external files twice * pipeline never redundantly saves the external data + more robust tokenizer * Stop saving tmp files, otherwise the engine looks for external files in the wrong place * Left pad support * cleanup * cleanup2 * Add in pipeline timing * add in force tokens logic * remove input validation for text generation pipelines * remove multitoken support for now * remove kv cache engine and other fixes * nest input shape override * comment out input shape override * add non batch override for ORT * clean up generation pipeline * initial commit * Update src/deepsparse/license.py * limit to 150mb * ready to review * fix the erronous Makefile * perhaps fixed GHA * take into consideration that GHA creates four files * initial commit * tested with actual model * remove val_inp argument * Update README.md * Apply suggestions from code review * Update README.md * [BugFix] Update deepsparse dockerfile (#1069) * Remove autoinstall triggering commands * Fix typo * initial implementation * working implementation for pipeline input * [Fix] Fix CLI benchmark errors (#1071) * initial commit * ready for review * Update src/deepsparse/utils/onnx.py * Clean a typo in the pipeline code * cleanup the old files * Update src/deepsparse/transformers/engines/nl_decoder_engine.py * ready for review * ready for testing * assert proper padding on pipeline init * now also supporting kv cache perplexity. time for cleanup * ready for review * correctly print engine info * work with left padding of the tokenizer * quality * fix the multitoken inference --------- Co-authored-by: corey-nm <[email protected]> Co-authored-by: Mark Kurtz <[email protected]> Co-authored-by: Benjamin <[email protected]> Co-authored-by: Rahul Tuli <[email protected]> * [Text Generation] Run deepsparse engine without the LIB.kv_cache object (#1108) * Update src/deepsparse/transformers/engines/nl_decoder_engine.py * fixed the logic to assert correct multibatch inference * fix integration tests * initial implementation * fix the integration test * better solution for fixing the issues caused by this PR in GHA * revert changes to yolo pipeline * Update src/deepsparse/transformers/engines/nl_decoder_engine.py Co-authored-by: Rahul Tuli <[email protected]> * response to Rahuls comments --------- Co-authored-by: Mark Kurtz <[email protected]> Co-authored-by: Benjamin <[email protected]> Co-authored-by: Rahul Tuli <[email protected]>

dbogunowicz and others added 30 commits June 5, 2023 15:55

initial commit

48ac0ac

Update src/deepsparse/license.py

cf7f2b9

Merge branch 'main' into feature/damian/do_not_save_to_tmp

832630a

Merge branch 'main' into feature/damian/do_not_save_to_tmp

9958c83

limit to 150mb

e6d2b03

ready to review

7f9935b

initial commit

b1cf01b

[Codegen][ORT][Static Seq Length] TextGenerationPipeline (#946)

0a3f48d

* initial commit * coreys simplifications * finishing the second model static * ready, time for beautification * ready for review * moved the code to examples * fix eos logic * add argument num_tokens_to_generate

reimplementation for generative pipelines

22d2746

restore text generation from examples

7f1651d

[CodeGen] ONNX model loading to support >2Gb models / two engines (#991)

b85746d

refactor sucessfull

aadc608

Pipeline fully refactored, time to test engine support. Note: Sliding…

58bc2b0

… window not yet implemented!

First iteration with Sage

d538444

Apply suggestions from code review

e19676b

ORT agrees with the Engine. But they both give not entirely correct r…

7908b74

…esult. Hey, this is good news still

dynamic ORT vs static DS

4bc3472

pipeline handles OPT multitoken pass

c07f7ed

fixes to get static pipeline a little further along

fb77838

adjust shapes and slicing to enable static autoregressive pass - ISSU…

2097463

…E: tokens past the base seq len are repeated

migrate from cache_length to positions input

5eb10a9

got if working for multitoken + single token scenario

9213f29

cleanup the pipeline

d9af004

further cleanup post merge

476f25d

Pipeline working for single-token inference only

fab44e4

do not load the onnx model with external files twice

d454e2f

pipeline never redundantly saves the external data + more robust toke…

1613e25

…nizer

Stop saving tmp files, otherwise the engine looks for external files …

b61055c

…in the wrong place

Left pad support

6ee25fc

dbogunowicz commented Jun 23, 2023

View reviewed changes

src/deepsparse/transformers/pipelines/text_generation.py Outdated Show resolved Hide resolved

dbogunowicz commented Jun 23, 2023

View reviewed changes

src/deepsparse/transformers/pipelines/text_generation.py Outdated Show resolved Hide resolved

dbogunowicz commented Jun 23, 2023

View reviewed changes

src/deepsparse/transformers/pipelines/text_generation.py Outdated Show resolved Hide resolved

dbogunowicz and others added 18 commits June 26, 2023 07:02

improvements after the sync with Mark

db6b54b

Merge branch 'feature/damian/fb_kv_cache' into feature/damian/kv_cach…

b3fb3b8

…e_ort

Merge remote-tracking branch 'origin/feature/damian/kv_cache_ort' int…

47c0c4b

…o feature/damian/decoder_engine

All changes applied, time for testing

76e332d

Merge remote-tracking branch 'origin/feature/damian/kv_cache_ort' int…

4791ed3

…o feature/damian/decoder_engine

Scaffolding to also run multitoken

8c5734b

add delay_overwriting_inputs

6c5daab

multitoken is working (although in limited capacity)

812408c

fix no kv cache inference

952abda

Do not create engine if not needed

2ff4987

remove the prefill option

725a210

fix docstring

108596e

remove prefill

f6a9baf

fix the computation of total cache capacity

b25886a

Merge remote-tracking branch 'origin/feature/damian/kv_cache_ort' int…

53d7b70

…o feature/damian/decoder_engine

merge

0b0f74a

Merge branch 'feature/damian/fb_kv_cache' into feature/damian/kv_cach…

4d6860a

…e_ort

Merge branch 'feature/damian/kv_cache_ort' into feature/damian/decode…

d68f045

…r_engine

bfineran suggested changes Jun 27, 2023

View reviewed changes

Base automatically changed from feature/damian/kv_cache_ort to feature/damian/fb_kv_cache June 28, 2023 10:23

dbogunowicz added 3 commits June 28, 2023 10:47

addressed PR comments

759dc93

merge

3e1d32f

quality

4c39d7f

dbogunowicz merged commit 0809aea into feature/damian/fb_kv_cache Jun 28, 2023

dbogunowicz deleted the feature/damian/decoder_engine branch June 28, 2023 12:18

dbogunowicz changed the title ~~[WiP] [KV Cache Interface] Text Generation & Decoder Engine Implementation~~ [KV Cache Interface] Text Generation & Decoder Engine Implementation Jun 28, 2023

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[KV Cache Interface] Text Generation & Decoder Engine Implementation #1089

[KV Cache Interface] Text Generation & Decoder Engine Implementation #1089

dbogunowicz commented Jun 22, 2023 •

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[KV Cache Interface] Text Generation & Decoder Engine Implementation #1089

[KV Cache Interface] Text Generation & Decoder Engine Implementation #1089

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dbogunowicz commented Jun 22, 2023 • edited Loading

No-cache inference

Single-token engine decoding only:

Single-token engine and multi-token engine decoding:

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dbogunowicz commented Jun 22, 2023 •

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