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Merged
sdpython merged 5 commits into from
Sep 9, 2025
Merged

add statistic on types #217

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3cc290a
add statistic on types
xadupre Sep 8, 2025
9bd2cf3
annot
xadupre Sep 8, 2025
2271777
fix missing variable
xadupre Sep 8, 2025
c42e4e1
fix validate
xadupre Sep 8, 2025
3a91a54
cache config
xadupre Sep 9, 2025
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142 changes: 142 additions & 0 deletions onnx_diagnostic/torch_models/hghub/hub_data_cached_configs.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -4687,3 +4687,145 @@ def _ccached_zai_glm_45():
},
}
)


def _ccached_microsoft_phi3_mini_128k_instruct():
"microsoft/Phi-3-mini-128k-instruct"
return transformers.Phi3Config(
**{
"_name_or_path": "Phi-3-mini-128k-instruct",
"architectures": ["Phi3ForCausalLM"],
"attention_dropout": 0.0,
"auto_map": {
"AutoConfig": "configuration_phi3.Phi3Config",
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM",
},
"bos_token_id": 1,
"embd_pdrop": 0.0,
"eos_token_id": 32000,
"hidden_act": "silu",
"hidden_size": 3072,
"initializer_range": 0.02,
"intermediate_size": 8192,
"max_position_embeddings": 131072,
"model_type": "phi3",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 32,
"original_max_position_embeddings": 4096,
"pad_token_id": 32000,
"resid_pdrop": 0.0,
"rms_norm_eps": 1e-05,
"rope_scaling": {
"long_factor": [
1.0700000524520874,
1.1200000047683716,
1.149999976158142,
1.4199999570846558,
1.5699999332427979,
1.7999999523162842,
2.129999876022339,
2.129999876022339,
3.009999990463257,
5.910000324249268,
6.950000286102295,
9.070000648498535,
9.930000305175781,
10.710000038146973,
11.130000114440918,
14.609999656677246,
15.409998893737793,
19.809999465942383,
37.279998779296875,
38.279998779296875,
38.599998474121094,
40.12000274658203,
46.20000457763672,
50.940006256103516,
53.66000747680664,
54.9373893737793,
56.89738845825195,
57.28738784790039,
59.98738479614258,
60.86738586425781,
60.887386322021484,
61.71739196777344,
62.91739273071289,
62.957393646240234,
63.41739273071289,
63.8173942565918,
63.83739471435547,
63.897396087646484,
63.93739700317383,
64.06739807128906,
64.11434936523438,
64.12435150146484,
64.15435028076172,
64.19435119628906,
64.24435424804688,
64.57435607910156,
64.69000244140625,
64.76000213623047,
],
"short_factor": [
1.1,
1.1,
1.1,
1.3000000000000003,
1.3500000000000003,
1.3500000000000003,
1.4000000000000004,
1.5500000000000005,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.000000000000001,
2.0500000000000007,
2.0500000000000007,
2.0500000000000007,
2.0500000000000007,
2.0500000000000007,
2.0500000000000007,
2.1000000000000005,
2.1000000000000005,
2.1500000000000004,
2.25,
2.25,
2.25,
2.25,
2.25,
2.3999999999999995,
2.4499999999999993,
2.499999999999999,
2.6999999999999984,
2.6999999999999984,
2.7499999999999982,
2.799999999999998,
2.8999999999999977,
3.049999999999997,
],
"type": "longrope",
},
"rope_theta": 10000.0,
"sliding_window": 262144,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.40.2",
"use_cache": true,
"attention_bias": false,
"vocab_size": 32064,
}
)
34 changes: 34 additions & 0 deletions onnx_diagnostic/torch_models/validate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -712,6 +712,7 @@ def validate_model(
print(f"[validate_model] done (dump onnx) in {duration}")
data["onnx_filename"] = onnx_filename
summary["time_onnx_save"] = duration
summary.update(compute_statistics(onnx_filename))
if verbose:
print(f"[validate_model] dumps statistics in {dump_folder!r}...")
dump_stats = os.path.join(dump_folder, f"{folder_name}.stats")
Expand Down Expand Up @@ -815,6 +816,39 @@ def validate_model(
return summary, data


def compute_statistics(onnx_filename: str) -> Dict[str, Union[float, int]]:
"""Computes some statistics on the model itself."""
onx = onnx.load(onnx_filename, load_external_data=False)

def node_iter(proto):
if isinstance(proto, onnx.ModelProto):
yield from node_iter(proto.graph)
for f in proto.functions:
yield from node_iter(f)
elif isinstance(proto, (onnx.FunctionProto, onnx.GraphProto)):
for node in proto.node:
yield node
for att in node.attribute:
if att.type == onnx.AttributeProto.GRAPH:
yield from node_iter(att.g)
if hasattr(proto, "initializer"):
yield from proto.initializer
else:
raise NotImplementedError(f"Unexpected type={type(proto)}")

counts: Dict[str, Union[float, int]] = {}
for proto in node_iter(onx):
if isinstance(proto, onnx.NodeProto):
key = f"n_node_{proto.op_type}"
else:
key = f"n_node_initializer_{proto.data_type}"

if key not in counts:
counts[key] = 0
counts[key] += 1
return counts


def _validate_do_run_model(
data, summary, key, tag, expected_tag, verbose, repeat, warmup, quiet
):
Expand Down
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