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Add support for an optional parameter in the example repeat int32 model #396

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Merged
merged 2 commits into from
Feb 20, 2025
Merged

Add support for an optional parameter in the example repeat int32 model #396

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pskiran1 Feb 16, 2025
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pskiran1 Feb 17, 2025
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15 changes: 13 additions & 2 deletions examples/decoupled/repeat_model.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# Copyright (c) 2022-2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
Expand Down Expand Up @@ -112,6 +112,14 @@ def initialize(self, args):
self.out_dtype = pb_utils.triton_string_to_numpy(out_config["data_type"])
self.idx_dtype = pb_utils.triton_string_to_numpy(idx_config["data_type"])

# Optional parameter to specify the number of elements in the OUT tensor in each response.
# Defaults to 1 if not provided. Example: If input 'IN' is [4] and 'output_num_elements' is set to 3,
# then 'OUT' will be [4, 4, 4]. If 'output_num_elements' is not specified, 'OUT' will default to [4].
parameters = self.model_config.get("parameters", {})
self.output_num_elements = int(
parameters.get("output_num_elements", {}).get("string_value", 1)
)

# To keep track of response threads so that we can delay
# the finalizing the model until all response threads
# have completed.
Expand Down Expand Up @@ -209,7 +217,10 @@ def response_thread(self, response_sender, in_input, delay_input):
time.sleep(delay_value / 1000)

idx_output = pb_utils.Tensor("IDX", numpy.array([idx], idx_dtype))
out_output = pb_utils.Tensor("OUT", numpy.array([in_value], out_dtype))
out_output = pb_utils.Tensor(
"OUT",
numpy.full((self.output_num_elements,), in_value, dtype=out_dtype),
)
response = pb_utils.InferenceResponse(
output_tensors=[idx_output, out_output]
)
Expand Down
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