diff --git a/HuggingFace/client.py b/HuggingFace/client.py index 784e69e2..75cf9af3 100644 --- a/HuggingFace/client.py +++ b/HuggingFace/client.py @@ -1,3 +1,29 @@ +# Copyright 2023, 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 * diff --git a/HuggingFace/ensemble_client.py b/HuggingFace/ensemble_client.py deleted file mode 100644 index 1a4e5d8a..00000000 --- a/HuggingFace/ensemble_client.py +++ /dev/null @@ -1,63 +0,0 @@ -# Copyright 2023, 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 * -from PIL import Image -import tritonclient.http as httpclient -import requests - -def main(): - client = httpclient.InferenceServerClient(url="localhost:8000") - - # Inputs - url = "http://images.cocodataset.org/val2017/000000039769.jpg" - image = np.asarray(Image.open(requests.get(url, stream=True).raw)).astype(np.float32) - image = np.expand_dims(image, axis=0) - - # Set Inputs - input_tensors = [ - httpclient.InferInput("image", image.shape, datatype="FP32") - ] - input_tensors[0].set_data_from_numpy(image) - - # Set outputs - outputs = [ - httpclient.InferRequestedOutput("last_hidden_state") - ] - - # Query - query_response = client.infer(model_name="ensemble_model", - inputs=input_tensors, - outputs=outputs) - - # Output - last_hidden_state = query_response.as_numpy("last_hidden_state") - print(last_hidden_state.shape) - -if __name__ == "__main__": - main() diff --git a/HuggingFace/python_backend_client.py b/HuggingFace/python_backend_client.py deleted file mode 100644 index 2805be20..00000000 --- a/HuggingFace/python_backend_client.py +++ /dev/null @@ -1,63 +0,0 @@ -# Copyright 2023, 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 * -from PIL import Image -import tritonclient.http as httpclient -import requests - -def main(): - client = httpclient.InferenceServerClient(url="localhost:8000") - - # Inputs - url = 'http://images.cocodataset.org/val2017/000000161642.jpg' - image = np.asarray(Image.open(requests.get(url, stream=True).raw)).astype(np.float32) - image = np.expand_dims(image, axis=0) - - # Set Inputs - input_tensors = [ - httpclient.InferInput("image", image.shape, datatype="FP32") - ] - input_tensors[0].set_data_from_numpy(image) - - # Set outputs - output_label = [ - httpclient.InferRequestedOutput("last_hidden_state") - ] - - # Query - query_response = client.infer(model_name="python_vit", - inputs=input_tensors, - outputs=output_label) - - # Output - last_hidden_state = query_response.as_numpy("last_hidden_state") - print(last_hidden_state.shape) - -if __name__ == "__main__": - main() diff --git a/Quick_Deploy/ONNX/config.pbtxt b/Quick_Deploy/ONNX/config.pbtxt deleted file mode 100644 index 566021bd..00000000 --- a/Quick_Deploy/ONNX/config.pbtxt +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright 2023, 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: "resnet" -backend: "onnxruntime" -max_batch_size: 8 -input: [ - { - name: "input" - data_type: TYPE_FP32 - dims: [3, 224, 224] - } -] -output: [ - { - name: "output" - data_type: TYPE_FP32 - dims: [1000] - } -] diff --git a/Quick_Deploy/ONNX/export.py b/Quick_Deploy/ONNX/export.py deleted file mode 100644 index e2b29ef2..00000000 --- a/Quick_Deploy/ONNX/export.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright 2023, 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 torch -import torchvision.models as models - -torch.hub._validate_not_a_forked_repo=lambda a,b,c: True - -# load model; We are going to use a pretrained resnet model -model = models.resnet50(pretrained=True).eval() -x = torch.randn(1, 3, 224, 224, requires_grad=True) - -# Export the model -torch.onnx.export(model, # model being run - x, # model input (or a tuple for multiple inputs) - "model.onnx", # where to save the model (can be a file or file-like object) - export_params=True, # store the trained parameter weights inside the model file - input_names = ['input'], # the model's input names - output_names = ['output'], # the model's output names - dynamic_axes = { - "input": { - 0: "batch" - } - } -)