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Merged
petermcaughan merged 5 commits into from
Apr 6, 2023
Merged

Petermca/whisper dedup #15365

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20cccf5
Add support for weight deduplication in beamsearch export
Apr 4, 2023
b716640
Reuse instead of duplicate code
Apr 4, 2023
06da586
Remove unnecessary import
Apr 4, 2023
047c4e5
Remove more unnecessary imports
Apr 4, 2023
1aae95a
Apply lintrunner
Apr 4, 2023
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21 changes: 16 additions & 5 deletions onnxruntime/python/tools/transformers/models/whisper/whisper_chain.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,13 @@
import os
import sys

import onnx
from onnx import TensorProto, helper
from transformers import WhisperConfig

sys.path.append(os.path.join(os.path.dirname(__file__), "..", ".."))
from convert_generation import get_shared_initializers # noqa: E402


def add_attention_mask(model):
# Add attention mask - required by BeamSearch but unused in Pytorch
Expand All @@ -13,11 +19,11 @@ def add_attention_mask(model):

def chain_model(args):
# Load encoder/decoder and insert necessary (but unused) graph inputs expected by BeamSearch op
encoder_model = onnx.load(args.encoder_path, load_external_data=True)
encoder_model = onnx.load_model(args.encoder_path, load_external_data=True)
encoder_model.graph.name = "encoderdecoderinit subgraph"
add_attention_mask(encoder_model)

decoder_model = onnx.load(args.decoder_path, load_external_data=True)
decoder_model = onnx.load_model(args.decoder_path, load_external_data=True)
decoder_model.graph.name = "decoder subgraph"
add_attention_mask(decoder_model)

Expand Down Expand Up @@ -48,8 +54,6 @@ def chain_model(args):
helper.make_attribute("no_repeat_ngram_size", args.no_repeat_ngram_size),
helper.make_attribute("early_stopping", True),
helper.make_attribute("model_type", 2),
helper.make_attribute("decoder", decoder_model.graph),
helper.make_attribute("encoder", encoder_model.graph),
]
)

Expand Down Expand Up @@ -85,7 +89,14 @@ def chain_model(args):
graph_outputs = [sequences]

# Initializers/opsets
initializers = []
# Delete shared data between decoder/encoder and move to larger graph initializers
initializers = get_shared_initializers(encoder_model, decoder_model)
node.attribute.extend(
[
helper.make_attribute("decoder", decoder_model.graph),
helper.make_attribute("encoder", encoder_model.graph),
]
)
opset_import = [helper.make_opsetid(domain="com.microsoft", version=1), helper.make_opsetid(domain="", version=17)]

beam_graph = helper.make_graph([node], "beam-search-test", graph_inputs, graph_outputs, initializers)
Expand Down