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test: Test and document histogram latency metrics #7694

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37 changes: 37 additions & 0 deletions docs/user_guide/metrics.md
Original file line number Diff line number Diff line change
Expand Up @@ -204,6 +204,43 @@ metrics are used for latencies:

To disable these metrics specifically, you can set `--metrics-config counter_latencies=false`

#### Histograms

> **Note**
>
> The following Histogram feature is experimental for the time being and may be
> subject to change based on user feedback.

By default, the following
[Histogram](https://prometheus.io/docs/concepts/metric_types/#histogram)
metrics are used for latencies:

|Category |Metric |Metric Name |Description |Granularity|Frequency |Model Type
|--------------|----------------|------------|---------------------------|-----------|-------------|-------------|
|Latency |Request to First Response Time |`nv_inference_first_response_histogram_ms` |Histogram of end-to-end inference request to the first response time |Per model |Per request | Decoupled |

To enable these metrics specifically, you can set `--metrics-config histogram_latencies=true`

Each histogram above is composed of several sub-metrics. For each histogram
metric, there is a set of `le` (less than or equal to) thresholds tracking
the counter for each bucket. Additionally, there are `_count` and `_sum`
metrics that aggregate the count and observed values for each. For example,
see the following information exposed by the "Time to First Response" histogram
metrics:
```
# HELP nv_first_response_histogram_ms Duration from request to first response in milliseconds
# TYPE nv_first_response_histogram_ms histogram
nv_inference_first_response_histogram_ms_count{model="my_model",version="1"} 37
nv_inference_first_response_histogram_ms_sum{model="my_model",version="1"} 10771
nv_inference_first_response_histogram_ms{model="my_model",version="1", le="100"} 8
nv_inference_first_response_histogram_ms{model="my_model",version="1", le="500"} 30
nv_inference_first_response_histogram_ms{model="my_model",version="1", le="2000"} 36
nv_inference_first_response_histogram_ms{model="my_model",version="1", le="5000"} 37
nv_inference_first_response_histogram_ms{model="my_model",version="1", le="+Inf"} 37
```

Triton initializes histograms with default buckets for each, as shown above. Customization of buckets per metric is currently unsupported.

#### Summaries

> **Note**
Expand Down
59 changes: 59 additions & 0 deletions qa/L0_metrics/ensemble_decoupled/async_execute_decouple/1/model.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,59 @@
# Copyright 2024, 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
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

import time

import numpy as np
import triton_python_backend_utils as pb_utils


class TritonPythonModel:
async def execute(self, requests):
request = requests[0]
wait_secs = pb_utils.get_input_tensor_by_name(
request, "WAIT_SECONDS"
).as_numpy()[0]
response_num = pb_utils.get_input_tensor_by_name(
request, "RESPONSE_NUM"
).as_numpy()[0]
output_tensors = [
pb_utils.Tensor("WAIT_SECONDS", np.array([wait_secs], np.float32)),
pb_utils.Tensor("RESPONSE_NUM", np.array([1], np.uint8)),
]

# Wait
time.sleep(wait_secs.item())
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response_sender = request.get_response_sender()
for i in range(response_num):
response = pb_utils.InferenceResponse(output_tensors)
if i != response_num - 1:
response_sender.send(response)
else:
response_sender.send(
response, flags=pb_utils.TRITONSERVER_RESPONSE_COMPLETE_FINAL
)

return None
Original file line number Diff line number Diff line change
@@ -0,0 +1,54 @@
# Copyright 2024, 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
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

backend: "python"
input [
{
name: "WAIT_SECONDS"
data_type: TYPE_FP32
dims: [ 1 ]
},
{
name: "RESPONSE_NUM"
data_type: TYPE_UINT8
dims: [ 1 ]
}
]
output [
{
name: "WAIT_SECONDS"
data_type: TYPE_FP32
dims: [ 1 ]
},
{
name: "RESPONSE_NUM"
data_type: TYPE_UINT8
dims: [ 1 ]
}
]

instance_group [{ kind: KIND_CPU }]
model_transaction_policy { decoupled: True }
89 changes: 89 additions & 0 deletions qa/L0_metrics/ensemble_decoupled/ensemble/config.pbtxt
Original file line number Diff line number Diff line change
@@ -0,0 +1,89 @@
# Copyright 2024, 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
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

name: "ensemble"
platform: "ensemble"
input [
{
name: "INPUT0"
data_type: TYPE_FP32
dims: [ 1 ]
},
{
name: "INPUT1"
data_type: TYPE_UINT8
dims: [ 1 ]
}
]
output [
{
name: "OUTPUT"
data_type: TYPE_FP32
dims: [ 1 ]
}
]
ensemble_scheduling {
step [
{
# decoupled model
model_name: "async_execute_decouple"
model_version: 1
input_map {
key: "WAIT_SECONDS"
value: "INPUT0"
}
input_map {
key: "RESPONSE_NUM"
value: "INPUT1"
}
output_map {
key: "WAIT_SECONDS"
value: "temp_output0"
}
output_map {
key: "RESPONSE_NUM"
value: "temp_output1"
}
},
{
# non-decoupled model
model_name: "async_execute"
model_version: 1
input_map {
key: "WAIT_SECONDS"
value: "temp_output0"
}
input_map {
key: "RESPONSE_NUM"
value: "temp_output1"
}
output_map {
key: "WAIT_SECONDS"
value: "OUTPUT"
}
}
]
}
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