disabled cuda for yamnet model, and removed multi-env setup scripts, revert back to single env
This commit is contained in:
@@ -1,3 +1,4 @@
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absl-py==2.1.0
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aiohappyeyeballs==2.4.4
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aiohttp==3.11.11
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aiosignal==1.3.2
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@@ -6,6 +7,7 @@ antlr4-python3-runtime==4.9.3
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appdirs==1.4.4
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asteroid==0.7.0
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asteroid-filterbanks==0.4.0
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astunparse==1.6.3
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attrs==25.1.0
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audioread==3.0.1
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billiard==4.2.1
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@@ -28,30 +30,42 @@ demucs==4.0.1
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dora_search==0.1.12
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einops==0.8.0
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filelock==3.17.0
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flatbuffers==25.2.10
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fonttools==4.55.6
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frozenlist==1.5.0
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fsspec==2024.12.0
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future==1.0.0
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gast==0.6.0
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google-pasta==0.2.0
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grpcio==1.70.0
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h5py==3.13.0
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huggingface-hub==0.28.0
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idna==3.10
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iniconfig==2.0.0
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Jinja2==3.1.5
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joblib==1.4.2
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julius==0.2.7
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keras==3.8.0
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kiwisolver==1.4.8
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kombu==5.4.2
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lameenc==1.8.1
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lazy_loader==0.4
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libclang==18.1.1
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librosa==0.10.2.post1
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lightning-utilities==0.11.9
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llvmlite==0.44.0
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loguru==0.7.3
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Markdown==3.7
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markdown-it-py==3.0.0
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MarkupSafe==3.0.2
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matplotlib==3.10.0
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mdurl==0.1.2
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mir_eval==0.7
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ml-dtypes==0.4.1
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mpmath==1.3.0
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msgpack==1.1.0
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multidict==6.1.0
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namex==0.0.8
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networkx==3.4.2
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numba==0.61.0
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numpy==1.26.4
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@@ -69,6 +83,8 @@ nvidia-nvjitlink-cu12==12.4.127
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nvidia-nvtx-cu12==12.4.127
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omegaconf==2.3.0
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openunmix==1.3.0
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opt_einsum==3.4.0
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optree==0.14.0
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packaging==23.2
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pandas==2.2.3
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pb-bss-eval==0.0.2
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@@ -79,7 +95,9 @@ pluggy==1.5.0
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pooch==1.8.2
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prompt_toolkit==3.0.50
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propcache==0.2.1
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protobuf==5.29.3
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pycparser==2.22
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Pygments==2.19.1
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pyparsing==3.2.1
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pystoi==0.4.1
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pytest==8.3.4
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@@ -91,6 +109,7 @@ PyYAML==6.0.2
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redis==5.2.1
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requests==2.32.3
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retrying==1.3.4
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rich==13.9.4
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scikit-learn==1.6.1
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scipy==1.15.1
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setuptools==75.8.0
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@@ -99,6 +118,12 @@ soundfile==0.13.1
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soxr==0.5.0.post1
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submitit==1.5.2
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sympy==1.13.1
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tensorboard==2.18.0
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tensorboard-data-server==0.7.2
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tensorflow==2.18.0
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tensorflow-hub==0.16.1
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termcolor==2.5.0
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tf_keras==2.18.0
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threadpoolctl==3.5.0
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torch==2.5.1
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torch-optimizer==0.1.0
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@@ -113,4 +138,7 @@ tzdata==2025.1
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urllib3==2.3.0
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vine==5.1.0
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wcwidth==0.2.13
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Werkzeug==3.1.3
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wheel==0.45.1
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wrapt==1.17.2
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yarl==1.18.3
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@@ -1,51 +0,0 @@
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absl-py==2.1.0
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astunparse==1.6.3
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certifi==2024.12.14
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charset-normalizer==3.4.1
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flatbuffers==25.1.24
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gast==0.6.0
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google-pasta==0.2.0
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grpcio==1.70.0
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h5py==3.12.1
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idna==3.10
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keras==3.8.0
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libclang==18.1.1
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Markdown==3.7
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markdown-it-py==3.0.0
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MarkupSafe==3.0.2
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mdurl==0.1.2
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ml-dtypes==0.4.1
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namex==0.0.8
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numpy==2.0.2
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nvidia-cublas-cu12==12.5.3.2
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nvidia-cuda-cupti-cu12==12.5.82
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nvidia-cuda-nvcc-cu12==12.5.82
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nvidia-cuda-nvrtc-cu12==12.5.82
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nvidia-cuda-runtime-cu12==12.5.82
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nvidia-cudnn-cu12==9.3.0.75
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nvidia-cufft-cu12==11.2.3.61
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nvidia-curand-cu12==10.3.6.82
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nvidia-cusolver-cu12==11.6.3.83
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nvidia-cusparse-cu12==12.5.1.3
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nvidia-nccl-cu12==2.21.5
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nvidia-nvjitlink-cu12==12.5.82
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opt_einsum==3.4.0
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optree==0.14.0
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packaging==24.2
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protobuf==5.29.3
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Pygments==2.19.1
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requests==2.32.3
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rich==13.9.4
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setuptools==75.8.0
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six==1.17.0
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tensorboard==2.18.0
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tensorboard-data-server==0.7.2
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tensorflow==2.18.0
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tensorflow-hub==0.16.1
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termcolor==2.5.0
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tf_keras==2.18.0
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typing_extensions==4.12.2
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urllib3==2.3.0
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Werkzeug==3.1.3
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wheel==0.45.1
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wrapt==1.17.2
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@@ -1,23 +0,0 @@
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#!/bin/bash
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# Define the paths for the environments
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ENV_1_PATH="envs/env"
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ENV_2_PATH="envs/env_tensorflow"
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# Check if the environments exist
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if [ ! -d "$ENV_1_PATH" ] || [ ! -d "$ENV_2_PATH" ]; then
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echo "One or both environments do not exist in the 'envs/' directory."
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exit 1
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fi
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# Activate the first environment (default)
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echo "Activating environment '$ENV_1_PATH'..."
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source "$ENV_1_PATH/bin/activate"
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# Export PYTHONPATH to include both environments' site-packages
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export PYTHONPATH="$PWD/$ENV_1_PATH/lib/python3.12/site-packages:$PWD/$ENV_2_PATH/lib/python3.12/site-packages"
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echo "Environment set up successfully. PYTHONPATH set to include both environments."
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# Optionally, print the current PYTHONPATH to verify
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echo "PYTHONPATH=${PYTHONPATH}"
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@@ -1,46 +0,0 @@
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#!/bin/bash
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# Check if the script is running in the root directory of the project
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PROJECT_ROOT="freq-split-enhance"
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CURRENT_DIR=$(basename "$PWD")
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if [ "$CURRENT_DIR" != "$PROJECT_ROOT" ]; then
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echo "This script must be run in the root directory of the project: '$PROJECT_ROOT'."
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exit 1
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fi
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# Check if the envs/ directory exists
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if [ ! -d "envs" ]; then
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echo "Directory 'envs/' does not exist. Please make sure it exists and contains the required environments. Please run the scripts/setup_env.sh script."
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exit 1
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fi
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# Check if the requirements/ directory exists, create it if not
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if [ ! -d "requirements" ]; then
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echo "Directory 'requirements/' does not exist. Creating it..."
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mkdir requirements
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fi
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# Function to freeze the dependencies of an environment
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freeze_env_deps() {
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local env_dir=$1
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local requirements_file=$2
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echo "Freezing dependencies for environment '$env_dir'..."
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source "$env_dir/bin/activate" # Activate the environment
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pip freeze > "$requirements_file" # Freeze the dependencies
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deactivate # Deactivate the environment
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echo "Dependencies for '$env_dir' saved to '$requirements_file'."
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}
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# Loop through all the environments inside envs/
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for env_dir in envs/*; do
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if [ -d "$env_dir" ]; then
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env_name=$(basename "$env_dir")
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requirements_file="requirements/$env_name.txt"
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freeze_env_deps "$env_dir" "$requirements_file"
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fi
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done
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echo "Dependencies for all environments have been successfully frozen."
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@@ -1,69 +0,0 @@
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#!/bin/bash
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# Check if the script is running in the root directory of the project
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PROJECT_ROOT="freq-split-enhance"
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CURRENT_DIR=$(basename "$PWD")
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if [ "$CURRENT_DIR" != "$PROJECT_ROOT" ]; then
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echo "This script must be run in the root directory of the project: '$PROJECT_ROOT'."
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exit 1
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fi
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# Check if the envs/ directory exists
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if [ ! -d "envs" ]; then
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echo "Directory 'envs/' does not exist. Please make sure it exists and contains the required environments. Please run the scripts/setup_env.sh script."
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exit 1
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fi
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# List all environments in the envs/ directory
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echo "Available environments:"
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env_count=0
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envs_list=()
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for env_dir in envs/*; do
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if [ -d "$env_dir" ]; then
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env_name=$(basename "$env_dir")
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envs_list+=("$env_name")
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echo "$((env_count + 1)). $env_name"
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((env_count++))
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fi
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done
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# Check if any environments exist
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if [ "$env_count" -eq 0 ]; then
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echo "No environments found in 'envs/'. Please create them first."
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exit 1
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fi
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# Ask the user to select an environment
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read -p "Select an environment (1-$env_count): " env_choice
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# Validate the user's choice
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if [[ ! "$env_choice" =~ ^[0-9]+$ ]] || [ "$env_choice" -lt 1 ] || [ "$env_choice" -gt "$env_count" ]; then
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echo "Invalid choice. Please select a number between 1 and $env_count."
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exit 1
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fi
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# Get the selected environment name
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selected_env="${envs_list[$((env_choice - 1))]}"
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# Ask the user for the module they want to install
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read -p "Enter the module you want to install in the '$selected_env' environment: " module_name
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# Function to install a module in the selected environment
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install_module() {
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local env_dir=$1
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local module=$2
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echo "Activating environment '$env_dir' and installing module '$module'..."
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source "$env_dir/bin/activate" # Activate the environment
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pip install "$module" # Install the module
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deactivate # Deactivate the environment
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echo "Module '$module' installed successfully in '$env_dir'."
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}
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# Install the module in the selected environment
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install_module "envs/$selected_env" "$module_name"
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echo "Module installation complete."
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@@ -1,32 +0,0 @@
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#!/bin/bash
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# Check if the script is running in the root directory of the project
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PROJECT_ROOT="freq-split-enhance"
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CURRENT_DIR=$(basename "$PWD")
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if [ "$CURRENT_DIR" != "$PROJECT_ROOT" ]; then
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echo "This script must be run in the root directory of the project: '$PROJECT_ROOT'."
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exit 1
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fi
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echo "Setting up virtual environments"
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mkdir envs
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#Create common env
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echo "Creating common virtual environment env"
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python -m venv envs/env
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#Create env for tensorflow
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echo "Creating virtual environment env_tensorflow"
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python -m venv envs/env_tensorflow
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source envs/env/bin/activate
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echo "Installing dependencies in virtual environment env"
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pip install -r requirements/env.txt
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deactivate
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source envs/env_tensorflow/bin/activate
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echo "Installing dependencies in virtual environment env_tensorflow"
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pip install -r requirements/env_tensorflow.txt
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deactivate
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@@ -5,6 +5,10 @@ import numpy as np
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import csv
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import os
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# Force TensorFlow to use only CPU
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tf.config.set_visible_devices([], 'GPU')
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model = hub.load('https://tfhub.dev/google/yamnet/1')
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#Find the name of the class with the top score when mean-aggregated across frames.
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