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Merge pull request #1 from NVIDIA-ISAAC-ROS/release-3.2
Isaac ROS 3.2
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‎.gitattributes‎

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# Ignore Python files in linguist
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*.py linguist-detectable=false
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# Images
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*.gif filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.png filter=lfs diff=lfs merge=lfs -text
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*.psd filter=lfs diff=lfs merge=lfs -text
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# Archives
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*.gz filter=lfs diff=lfs merge=lfs -text
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*.tar filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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# Documents
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*.pdf filter=lfs diff=lfs merge=lfs -text
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# Shared libraries
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*.so filter=lfs diff=lfs merge=lfs -text
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*.so.* filter=lfs diff=lfs merge=lfs -text
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# ROS Bags
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**/resources/**/*.zstd filter=lfs diff=lfs merge=lfs -text
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**/resources/**/*.db3 filter=lfs diff=lfs merge=lfs -text
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**/resources/**/*.yaml filter=lfs diff=lfs merge=lfs -text

‎.gitignore‎

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# Ignore all pycache files
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**/__pycache__/**

‎README.md‎

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# My Repository
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This is my new repository.
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# Isaac ROS Data Tools
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Tools for inspecting and validating data sent through graphs containing Isaac ROS nodes.
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---
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## Latest
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Update 2024-12-10: Initial release

‎isaac_ros_tensor_inspector/isaac_ros_tensor_inspector/__init__.py‎

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# SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
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# Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# SPDX-License-Identifier: Apache-2.0

‎isaac_ros_tensor_inspector/isaac_ros_tensor_inspector/tensor_inspector.py‎

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# SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
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# Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# SPDX-License-Identifier: Apache-2.0
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import struct
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from isaac_ros_tensor_list_interfaces.msg import Tensor, TensorList
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import numpy as np
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import rclpy
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from rclpy.node import Node
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class TensorInspectorNode(Node):
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# Conversion map from Tensor.msg's data types to Python types
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MSG_TO_PYTHON_MAP = {
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# data_type_number : ('struct_specifier', num_bytes)
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1: ('b', 1), # int8
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2: ('B', 1), # uint8
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3: ('h', 2), # int16
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4: ('H', 2), # uint16
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5: ('i', 4), # int32
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6: ('I', 4), # uint32
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7: ('q', 8), # int64
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8: ('Q', 8), # uint64
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9: ('f', 4), # float32
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10: ('d', 8) # float64
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}
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# Conversion map from Numpy types to Tensor.msg's data types
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PYTHON_TO_MSG_MAP = {
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# dtype : data_type_number
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np.dtype('int8'): 1,
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np.dtype('uint8'): 2,
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np.dtype('int16'): 3,
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np.dtype('uint16'): 4,
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np.dtype('int32'): 5,
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np.dtype('uint32'): 6,
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np.dtype('int64'): 7,
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np.dtype('uint64'): 8,
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np.dtype('float32'): 9,
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np.dtype('float64'): 10
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}
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def __init__(self):
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super().__init__('tensor_inspector')
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# Input side: whether or not to save the original tensor received
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self.subscription = self.create_subscription(
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TensorList,
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'original_tensor',
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self.listener_callback,
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10)
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self.declare_parameter('original_tensor_npz_path', '')
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self.original_tensor_npz_path = self.get_parameter(
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'original_tensor_npz_path').get_parameter_value().string_value
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self.should_save_original = len(self.original_tensor_npz_path) > 0
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if self.should_save_original:
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self.get_logger().info(
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f'Original tensor received will be saved to {self.original_tensor_npz_path}')
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# Output side: whether or not to replace the original tensor with an edited one
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self.publisher = self.create_publisher(
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TensorList,
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'edited_tensor',
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10)
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self.declare_parameter('edited_tensor_npz_path', '')
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edited_tensor_npz_path = self.get_parameter(
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'edited_tensor_npz_path').get_parameter_value().string_value
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self.should_edit = len(edited_tensor_npz_path) > 0
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if self.should_edit:
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self.edited_tensor_data = np.load(edited_tensor_npz_path)
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self.get_logger().info(
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f'Edited tensor will be loaded from {edited_tensor_npz_path}')
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def listener_callback(self, msg):
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if self.should_save_original:
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tensor_dict = {}
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for tensor in msg.tensors:
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dims = tensor.shape.dims
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N = np.prod(dims)
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self.get_logger().debug(
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f'Tensor {tensor.name} with dims {dims} has N={N} elements')
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conversion = self.MSG_TO_PYTHON_MAP.get(tensor.data_type)
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if conversion is None:
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self.get_logger().error(
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f'Original tensor {tensor.name} has unknown data type {tensor.data_type}')
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continue
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element_format, element_num_bytes = conversion
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elements = []
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for i in range(N):
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# Interpret tensor fields as particular numeric type from bytes
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element = struct.unpack(f'<{element_format}', tensor.data[
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element_num_bytes * i:
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element_num_bytes * (i + 1)
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])[0] # struct.unpack returns a tuple with one element
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elements.append(element)
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# Add element as numpy array to dictionary
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tensor_dict[tensor.name] = np.resize(elements, dims)
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np.savez(self.original_tensor_npz_path, **tensor_dict)
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self.get_logger().debug('Saved original tensor')
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if self.should_edit:
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tensors = []
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for tensor_name, tensor_npz in self.edited_tensor_data.items():
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# Create new tensor from data
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tensor = Tensor()
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tensor.name = tensor_name
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tensor.shape.rank = len(tensor_npz.shape)
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tensor.shape.dims = tensor_npz.shape
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element_data_type = self.PYTHON_TO_MSG_MAP.get(tensor_npz.dtype)
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if element_data_type is None:
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self.get_logger().error(
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f'Edited tensor {tensor.name} has unknown data type {tensor_npz.dtype}')
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continue
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tensor.data_type = element_data_type
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tensor.strides = tensor_npz.strides
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tensor.data = tensor_npz.tobytes()
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tensors.append(tensor)
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# Overwrite original tensors with new tensors
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msg.tensors = tensors
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self.get_logger().debug('Edited tensor')
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self.publisher.publish(msg)
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self.get_logger().debug('Published tensor message')
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def main(args=None):
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rclpy.init(args=args)
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node = TensorInspectorNode()
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rclpy.spin(node)
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rclpy.shutdown()
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if __name__ == '__main__':
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main()

‎isaac_ros_tensor_inspector/package.xml‎

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<?xml version="1.0"?>
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<?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?>
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<package format="3">
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<name>isaac_ros_tensor_inspector</name>
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<version>3.2.0</version>
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<description>Tools for inspecting and verifying TensorList messages</description>
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<maintainer email="[email protected]">Isaac ROS Maintainers</maintainer>
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<license>Apache-2.0</license>
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<url type="website">https://developer.nvidia.com/isaac-ros/</url>
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<author>Jaiveer Singh</author>
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<build_depend>isaac_ros_common</build_depend>
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<depend>isaac_ros_tensor_list_interfaces</depend>
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<test_depend>ament_copyright</test_depend>
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<test_depend>ament_flake8</test_depend>
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<test_depend>ament_pep257</test_depend>
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<test_depend>python3-pytest</test_depend>
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<export>
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<build_type>ament_python</build_type>
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</export>
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</package>

‎isaac_ros_tensor_inspector/resource/isaac_ros_tensor_inspector‎

Whitespace-only changes.

‎isaac_ros_tensor_inspector/scripts/tensor_comparator.py‎

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#!/usr/bin/env python3
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# SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
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# Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# SPDX-License-Identifier: Apache-2.0
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import argparse as ap
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import math
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from pathlib import Path
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import numpy as np
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def compare(
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tensor1_path: Path,
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tensor2_path: Path,
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output_directory: Path,
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rel_tol: float,
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abs_tol: float
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):
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tensor_list1 = np.load(tensor1_path, allow_pickle=True)
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tensor_list2 = np.load(tensor2_path, allow_pickle=True)
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assert len(tensor_list1.keys()) == len(tensor_list2.keys()), \
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'Tensor lists are not the same length'
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logfile_path = output_directory / \
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f'comparator_logfile_{tensor1_path.stem}_{tensor2_path.stem}.txt'
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print(f'Logfile path: {logfile_path}')
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with open(logfile_path, 'w+') as logfile:
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for tensor1_name, tensor2_name in zip(tensor_list1, tensor_list2):
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print(f'T1 name: \t{tensor1_name}')
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print(f'T2 name: \t{tensor2_name}')
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tensor1, tensor2 = tensor_list1[tensor1_name], tensor_list2[tensor2_name]
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print(f'T1 shape: \t{tensor1.shape}')
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print(f'T2 shape: \t{tensor2.shape}')
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count_good, count_bad = 0, 0
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logfile.write(
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f'Comparing: {tensor1_path.name} vs. {tensor2_path.name}\n')
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logfile.write(
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f'Relative Tolerance: {rel_tol} \tAbsolute Tolerance: {abs_tol}\n\n')
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for (index1, e1), (index2, e2) in zip(
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np.ndenumerate(tensor1), np.ndenumerate(tensor2)
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):
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status_string = ''
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if math.isclose(e1, e2, rel_tol=rel_tol, abs_tol=abs_tol):
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count_good += 1
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status_string = 'GOOD'
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else:
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count_bad += 1
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status_string = 'BAD'
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logfile.writelines([
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status_string + '\n',
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f'T1 \t{index1}: {e1:.10f}\n',
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f'T2 \t{index2}: {e2:.10f}\n',
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'\n'
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])
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logfile.write(f'Count GOOD: {count_good} vs. Count BAD: {count_bad}\n')
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print(f'Count GOOD: {count_good}')
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print(f'Count BAD: {count_bad}')
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if __name__ == '__main__':
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parser = ap.ArgumentParser()
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parser.add_argument('tensor1_filename')
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parser.add_argument('tensor2_filename')
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parser.add_argument('output_directory')
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parser.add_argument('--abs-tol', '-a', default=0.0, type=float,
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help='Absolute numerical error acceptable per element')
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parser.add_argument('--rel-tol', '-r', default=0.05, type=float,
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help='Relative percentage error acceptable per element')
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args = parser.parse_args()
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compare(Path(args.tensor1_filename), Path(args.tensor2_filename), Path(args.output_directory),
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rel_tol=args.rel_tol, abs_tol=args.abs_tol)

‎isaac_ros_tensor_inspector/setup.cfg‎

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[develop]
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script_dir=$base/lib/isaac_ros_tensor_inspector
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[install]
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install_scripts=$base/lib/isaac_ros_tensor_inspector

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