Skip to content

Support broadcast expand in naive_call_method_expand_pass. #598

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
TelGome wants to merge 1 commit into
base: develop
Choose a base branch
from
Open

Support broadcast expand in naive_call_method_expand_pass. #598

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 5 additions & 4 deletions graph_net/torch/dim_gen_passes/naive_call_method_expand_pass.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,10 +13,7 @@ def get_pass_name(cls) -> bool:
def need_rewrite(self, traced_module: fx.GraphModule) -> bool:
if 0 not in self.axes:
return False
for node in traced_module.graph.nodes:
if node.op == "call_method" and node.target == "expand":
return True
return False
return any(self._node_need_rewrite(node) for node in traced_module.graph.nodes)

def _node_need_rewrite(self, node) -> bool:
if not (node.op == "call_method"):
Expand Down Expand Up @@ -91,6 +88,10 @@ def rewrite(self, traced_module: fx.GraphModule) -> fx.GraphModule:
else:
# Do nothing.
pass
elif axis_idx == 0 and input_dim_size == 1 and target_dim > 1:
matched_axis = 0
else:
pass

if matched_axis != -1:
# Found a matching dynamic axis (matched_axis), replace it with a size() call
Expand Down
55 changes: 54 additions & 1 deletion samples/transformers-auto-model/mmarco-mMiniLMv2-L12-H384-v1/graph_net.json
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1 +1,54 @@
{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "model_name": "cross-encoder/mmarco-mMiniLMv2-L12-H384-v1", "source": "huggingface_hub", "original_tag": ["sentence-transformers", "pytorch", "onnx", "safetensors", "openvino", "xlm-roberta", "text-classification", "transformers", "text-ranking", "en", "ar", "zh", "nl", "fr", "de", "hi", "in", "it", "ja", "pt", "ru", "es", "vi", "multilingual", "dataset:unicamp-dl/mmarco", "base_model:nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large", "base_model:quantized:nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large", "license:apache-2.0", "region:us"], "heuristic_tag": "nlp", "dimension_generalization_passes": ["naive_call_method_view_pass", "tuple_arg_call_method_view_pass", "naive_call_method_reshape_pass", "naive_call_method_expand_pass", "non_batch_call_method_expand_pass", "non_batch_call_function_arange_pass", "non_batch_call_function_getitem_slice_pass", "non_batch_call_function_full_pass", "non_batch_call_function_full_plus_one_pass", "non_batch_call_function_zeros_pass", "non_batch_call_function_arange_plus_one_pass"]}
{
"framework": "torch",
"num_devices_required": 1,
"num_nodes_required": 1,
"dynamic": false,
"model_name": "cross-encoder/mmarco-mMiniLMv2-L12-H384-v1",
"source": "huggingface_hub",
"original_tag": [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"openvino",
"xlm-roberta",
"text-classification",
"transformers",
"text-ranking",
"en",
"ar",
"zh",
"nl",
"fr",
"de",
"hi",
"in",
"it",
"ja",
"pt",
"ru",
"es",
"vi",
"multilingual",
"dataset:unicamp-dl/mmarco",
"base_model:nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large",
"base_model:quantized:nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large",
"license:apache-2.0",
"region:us"
],
"heuristic_tag": "nlp",
"dimension_generalization_passes": [
"batch_call_method_view_pass",
"tuple_arg_call_method_view_pass",
"naive_call_method_reshape_pass",
"naive_call_method_expand_pass",
"non_batch_call_method_expand_pass",
"non_batch_call_function_arange_pass",
"non_batch_call_function_getitem_slice_pass",
"non_batch_call_function_full_pass",
"non_batch_call_function_full_plus_one_pass",
"non_batch_call_function_zeros_pass",
"non_batch_call_function_arange_plus_one_pass"
],
"symbolic_dimension_reifier": "naive_nlp_sym_dim_reifier"
}
521 changes: 261 additions & 260 deletions samples/transformers-auto-model/mmarco-mMiniLMv2-L12-H384-v1/input_tensor_constraints.py
View file
Open in desktop

Large diffs are not rendered by default.

42 changes: 41 additions & 1 deletion samples/transformers-auto-model/msmarco-MiniLM-L12-en-de-v1/graph_net.json
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1 +1,41 @@
{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "model_name": "cross-encoder/msmarco-MiniLM-L12-en-de-v1", "source": "huggingface_hub", "original_tag": ["sentence-transformers", "pytorch", "onnx", "safetensors", "openvino", "bert", "text-classification", "transformers", "text-ranking", "en", "de", "dataset:sentence-transformers/msmarco", "base_model:microsoft/Multilingual-MiniLM-L12-H384", "base_model:quantized:microsoft/Multilingual-MiniLM-L12-H384", "license:apache-2.0", "region:us"], "heuristic_tag": "nlp", "dimension_generalization_passes": ["naive_call_method_view_pass", "tuple_arg_call_method_view_pass", "naive_call_method_reshape_pass", "naive_call_method_expand_pass", "non_batch_call_method_expand_pass", "non_batch_call_function_arange_pass", "non_batch_call_function_getitem_slice_pass", "non_batch_call_function_full_pass", "non_batch_call_function_full_plus_one_pass", "non_batch_call_function_zeros_pass", "non_batch_call_function_arange_plus_one_pass"]}
{
"framework": "torch",
"num_devices_required": 1,
"num_nodes_required": 1,
"dynamic": false,
"model_name": "cross-encoder/msmarco-MiniLM-L12-en-de-v1",
"source": "huggingface_hub",
"original_tag": [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"openvino",
"bert",
"text-classification",
"transformers",
"text-ranking",
"en",
"de",
"dataset:sentence-transformers/msmarco",
"base_model:microsoft/Multilingual-MiniLM-L12-H384",
"base_model:quantized:microsoft/Multilingual-MiniLM-L12-H384",
"license:apache-2.0",
"region:us"
],
"heuristic_tag": "nlp",
"dimension_generalization_passes": [
"batch_call_method_view_pass",
"tuple_arg_call_method_view_pass",
"naive_call_method_reshape_pass",
"naive_call_method_expand_pass",
"non_batch_call_method_expand_pass",
"non_batch_call_function_arange_pass",
"non_batch_call_function_getitem_slice_pass",
"non_batch_call_function_full_pass",
"non_batch_call_function_full_plus_one_pass",
"non_batch_call_function_zeros_pass",
"non_batch_call_function_arange_plus_one_pass"
],
"symbolic_dimension_reifier": "naive_nlp_sym_dim_reifier"
}
Loading