Add Copyrights (triton-inference-server#4968)

* Autoformat and add copyrights

* Add copyright

docs/conf.py

@@ -44,7 +44,6 @@
 # import sys
 # sys.path.insert(0, os.path.abspath('.'))
 
-
 # -- Project information -----------------------------------------------------
 
 project = 'NVIDIA Triton Inference Server'
@@ -102,10 +101,7 @@
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
 # This pattern also affects html_static_path and html_extra_path.
-exclude_patterns = [
-  "README.md"
-]
-
+exclude_patterns = ["README.md"]
 
 # -- Options for HTML output -------------------------------------------------
 
@@ -154,8 +150,11 @@
 deploy_ngc_org = "nvidia"
 deploy_ngc_team = "triton"
 myst_substitutions = {
-    "VersionNum": version_short,
-    "deploy_ngc_org_team": f"{deploy_ngc_org}/{deploy_ngc_team}" if deploy_ngc_team else deploy_ngc_org,
+    "VersionNum":
+        version_short,
+    "deploy_ngc_org_team":
+        f"{deploy_ngc_org}/{deploy_ngc_team}"
+        if deploy_ngc_team else deploy_ngc_org,
 }
 
 
@@ -168,9 +167,13 @@ def ultimateReplace(app, docname, source):
 
 # this is a necessary hack to allow us to fill in variables that exist in code blocks
 ultimate_replacements = {
-    "{VersionNum}": version_short,
-    "{SamplesVersionNum}": version_short,
-    "{NgcOrgTeam}": f"{deploy_ngc_org}/{deploy_ngc_team}" if deploy_ngc_team else deploy_ngc_org,
+    "{VersionNum}":
+        version_short,
+    "{SamplesVersionNum}":
+        version_short,
+    "{NgcOrgTeam}":
+        f"{deploy_ngc_org}/{deploy_ngc_team}"
+        if deploy_ngc_team else deploy_ngc_org,
 }
 
 #bibtex_bibfiles = ["references.bib"]
@@ -210,7 +213,8 @@ def setup(app):
 
 # Patch for sphinx.search stemming short terms (i.e. tts -> tt)
 # https://github.com/sphinx-doc/sphinx/blob/4.5.x/sphinx/search/__init__.py#L380
-def sphinxSearchIndexFeed(self, docname: str, filename: str, title: str, doctree: nodes.document):
+def sphinxSearchIndexFeed(self, docname: str, filename: str, title: str,
+                          doctree: nodes.document):
     """Feed a doctree to the index."""
     self._titles[docname] = title
     self._filenames[docname] = filename
@@ -238,9 +242,11 @@ def stem(word: str) -> str:
     for word in visitor.found_words:
         stemmed_word = stem(word)
         # again, stemmer must not remove words from search index
-        if len(stemmed_word) <= 3 or not _filter(stemmed_word) and _filter(word):
+        if len(stemmed_word) <= 3 or not _filter(stemmed_word) and _filter(
+                word):
             stemmed_word = word.lower()
-        already_indexed = docname in self._title_mapping.get(stemmed_word, set())
+        already_indexed = docname in self._title_mapping.get(
+            stemmed_word, set())
         if _filter(stemmed_word) and not already_indexed:
             self._mapping.setdefault(stemmed_word, set()).add(docname)
 

docs/examples/README.md

@@ -1,3 +1,31 @@
+<!--
+# Copyright 2022, 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.
+-->
+
 # Triton Examples
 
 This folder contains the following:

docs/examples/stable_diffusion/README.md

@@ -1,3 +1,31 @@
+<!--
+# Copyright 2022, 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.
+-->
+
 # Stable diffusion
 
 *Note*: This tutorial aims at demonstrating the ease of deployment and doesn't incorporate all possible optimizations using the NVIDIA ecosystem.

docs/examples/stable_diffusion/client.py

@@ -1,3 +1,29 @@
+# Copyright (c) 2022, 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 numpy as np
 import time
 from tritonclient.utils import *
@@ -11,16 +37,15 @@ def main():
     prompt = "Pikachu with a hat, 4k, 3d render"
     text_obj = np.array([prompt], dtype="object").reshape((-1, 1))
 
-    input_text = httpclient.InferInput(
-        "prompt", text_obj.shape, np_to_triton_dtype(text_obj.dtype)
-    )
+    input_text = httpclient.InferInput("prompt", text_obj.shape,
+                                       np_to_triton_dtype(text_obj.dtype))
     input_text.set_data_from_numpy(text_obj)
 
     output_img = httpclient.InferRequestedOutput("generated_image")
 
-    query_response = client.infer(
-        model_name="pipeline", inputs=[input_text], outputs=[output_img]
-    )
+    query_response = client.infer(model_name="pipeline",
+                                  inputs=[input_text],
+                                  outputs=[output_img])
 
     image = query_response.as_numpy("generated_image")
     im = Image.fromarray(np.squeeze(image.astype(np.uint8)))

docs/examples/stable_diffusion/export.py

@@ -1,11 +1,37 @@
+# Copyright (c) 2022, 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.
+
 from diffusers import AutoencoderKL
 from transformers import CLIPTextModel, CLIPTokenizer
 import torch
 
 prompt = "Draw a dog"
-vae = AutoencoderKL.from_pretrained(
-    "CompVis/stable-diffusion-v1-4", subfolder="vae", use_auth_token=True
-)
+vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4",
+                                    subfolder="vae",
+                                    use_auth_token=True)
 
 tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14")
 text_encoder = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14")
@@ -18,7 +44,12 @@
     input_names=["latent_sample", "return_dict"],
     output_names=["sample"],
     dynamic_axes={
-        "latent_sample": {0: "batch", 1: "channels", 2: "height", 3: "width"},
+        "latent_sample": {
+            0: "batch",
+            1: "channels",
+            2: "height",
+            3: "width"
+        },
     },
     do_constant_folding=True,
     opset_version=14,
@@ -39,7 +70,10 @@
     input_names=["input_ids"],
     output_names=["last_hidden_state", "pooler_output"],
     dynamic_axes={
-        "input_ids": {0: "batch", 1: "sequence"},
+        "input_ids": {
+            0: "batch",
+            1: "sequence"
+        },
     },
     opset_version=14,
     do_constant_folding=True,

docs/examples/stable_diffusion/gui/README.md

@@ -1,3 +1,31 @@
+<!--
+# Copyright 2022, 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.
+-->
+
 # Stable Diffusion UI
 A simple Gradio UI for communicating with Stable Diffusion on Triton
 

docs/examples/stable_diffusion/gui/client.py

@@ -1,3 +1,29 @@
+# Copyright (c) 2022, 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 argparse
 
 import gradio as gr
@@ -10,22 +36,20 @@
 parser.add_argument("--triton_url", default="localhost:8001")
 args = parser.parse_args()
 
-
 client = grpcclient.InferenceServerClient(url=f"{args.triton_url}")
 
 
 def generate(prompt):
     text_obj = np.array([prompt], dtype="object").reshape((-1, 1))
-    input_text = grpcclient.InferInput(
-        "prompt", text_obj.shape, np_to_triton_dtype(text_obj.dtype)
-    )
+    input_text = grpcclient.InferInput("prompt", text_obj.shape,
+                                       np_to_triton_dtype(text_obj.dtype))
     input_text.set_data_from_numpy(text_obj)
 
     output_img = grpcclient.InferRequestedOutput("generated_image")
 
-    response = client.infer(
-        model_name="pipeline", inputs=[input_text], outputs=[output_img]
-    )
+    response = client.infer(model_name="pipeline",
+                            inputs=[input_text],
+                            outputs=[output_img])
     resp_img = response.as_numpy("generated_image")
     print(resp_img.shape)
     im = Image.fromarray(np.squeeze(resp_img.astype(np.uint8)))