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Nov 3, 2023
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Test data for two resizes with shared subgraphs #1115

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5168d7d
Test data for two resizes with shared subgraphs
dkurt Oct 27, 2023
b907d6d
Add extra node
dkurt Oct 31, 2023
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58 changes: 57 additions & 1 deletion testdata/dnn/onnx/generate_onnx_models_with_onnxscript.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ def make_model_and_data(model, *args, **kwargs):
np.save(input_file, inputs[0])
else:
for idx, input in enumerate(inputs, start=0):
input_files = os.path.join("data", "input_" + name + "_" + str(index))
input_files = os.path.join("data", "input_" + name + "_" + str(idx))
np.save(input_files, input)
if "force_saving_output_as_dtype_float32" in kwargs and kwargs["force_saving_output_as_dtype_float32"]:
output = output.astype(np.float32)
Expand Down Expand Up @@ -68,3 +68,59 @@ def greater_input_dtype_int64(x: ost.FLOAT[27, 9]) ->ost.BOOL[27, 9]:
y = op.Greater(x, op.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [], np.array([61], dtype=np.int64))))
return y
make_model_and_data(greater_input_dtype_int64, np.random.randint(0, 100, size=[27, 9], dtype=np.int64), force_saving_input_as_dtype_float32=True, force_saving_output_as_dtype_float32=True)

from onnxscript import opset11

@ost.script()
def two_resizes_with_shared_subgraphs(x: ost.FLOAT["batch", 1, "height", "width"], y: ost.FLOAT[1, 1, 3, 2], z: ost.FLOAT[1, 1, 2, 1]) ->ost.FLOAT["batch", 1, "height", "width"]:
shape_src_1 = opset11.Shape(x)
shape_src_2 = opset11.Shape(x)
gather_h = opset11.Gather(shape_src_1, opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [], np.array([2], dtype=np.int64))), axis=0)
gather_w = opset11.Gather(shape_src_2, opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [], np.array([3], dtype=np.int64))), axis=0)
unsqueeze_w_1 = opset11.Unsqueeze(gather_w, axes=[0])
unsqueeze_w_2 = opset11.Unsqueeze(gather_w, axes=[0])
unsqueeze_h_1 = opset11.Unsqueeze(gather_h, axes=[0])
unsqueeze_h_2 = opset11.Unsqueeze(gather_h, axes=[0])
concat_1 = opset11.Cast(opset11.Concat(unsqueeze_h_1, unsqueeze_w_1, axis=0), to=ost.INT64.dtype)
concat_2 = opset11.Cast(opset11.Concat(unsqueeze_h_2, unsqueeze_w_2, axis=0), to=ost.INT64.dtype)

# This op is required to test double node removal
y = opset11.Add(y, opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.FLOAT, [1], np.array([0.5], dtype=np.float32))))

# First branch
sliced = opset11.Slice(opset11.Shape(y),
starts=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [1], np.array([0], dtype=np.int64))),
ends=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [1], np.array([2], dtype=np.int64))),
axes=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [1], np.array([0], dtype=np.int64))),
)
concat_y = opset11.Concat(sliced, concat_1, axis=0)
resized_y = opset11.Resize(y,
roi=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.FLOAT, [0], np.empty([0]))),
scales=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.FLOAT, [0], np.empty([0]))),
sizes=concat_y,
coordinate_transformation_mode='pytorch_half_pixel',
cubic_coeff_a=-0.75,
mode='linear',
nearest_mode='floor'
)

# Second branch
sliced = opset11.Slice(opset11.Shape(z),
starts=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [1], np.array([0], dtype=np.int64))),
ends=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [1], np.array([2], dtype=np.int64))),
axes=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.INT64, [1], np.array([0], dtype=np.int64))),
)
concat_z = opset11.Concat(sliced, concat_2, axis=0)
resized_z = opset11.Resize(z,
roi=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.FLOAT, [0], np.empty([0]))),
scales=opset11.Constant(value=onnx.helper.make_tensor("", onnx.TensorProto.FLOAT, [0], np.empty([0]))),
sizes=concat_z,
coordinate_transformation_mode='pytorch_half_pixel',
cubic_coeff_a=-0.75,
mode='linear',
nearest_mode='floor'
)

return opset11.Add(resized_y, resized_z)

make_model_and_data(two_resizes_with_shared_subgraphs, np.random.rand(1, 1, 4, 5).astype(np.float32), np.random.rand(1, 1, 3, 2).astype(np.float32), np.random.rand(1, 1, 2, 1).astype(np.float32))
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