Merge branch 'main' of https://github.com/unifyai/ivy into fix_key_arg_1

.devcontainer/build_gpu/devcontainer.json

@@ -2,11 +2,11 @@
 	"name": "Ivy GPU Development Environment (build)",
 
 	"build": {
-		"dockerfile": "../../docker/DockerfileGPUMultiCuda",
+		"dockerfile": "../../docker/DockerfileGPU",
 		"context": "../..",
 		"args": {
-            "IMAGE_NAME": "unifyai/multicuda",
-            "IMAGE_TAG": "base_and_requirements"
+            "IMAGE_NAME": "unifyai/ivy",
+            "IMAGE_TAG": "latest-gpu"
         }
 	},
 

.devcontainer/image_gpu/devcontainer.json

@@ -1,7 +1,7 @@
 {
 	"name": "Ivy GPU Development Environment (image)",
 
-	"image": "unifyai/multicuda:base_and_requirements",
+	"image": "unifyai/ivy:latest-gpu",
 	"customizations": {
 		"vscode": {
 			"extensions": [

.github/workflows/dockerfile-gpu-push.yml

@@ -0,0 +1,26 @@
+name: GPU Dockerfile Push
+
+on:
+  schedule:
+    - cron: '0 0 * * *'
+  workflow_dispatch:
+
+jobs:
+
+  build:
+    runs-on: ubuntu-latest-4-cores
+
+    steps:
+      - name: Checkout 🛎 Ivy
+        uses: actions/checkout@v3
+
+      - name: Login to Docker Hub
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+      - name: Build and push GPU image
+        run: |
+          docker build --progress=plain --no-cache -t unifyai/ivy:latest-gpu -f docker/DockerfileGPU .
+          docker push unifyai/ivy:latest-gpu

.github/workflows/intelligent-tests-pr.yml

@@ -1,12 +1,10 @@
 name: intelligent-tests-pr
 on:
   workflow_dispatch:
-  pull_request_target:
-    types: [labeled, opened, synchronize, reopened, review_requested]
+  pull_request:
 
 permissions:
   actions: read
-  pull-requests: write
 
 jobs:
   display_test_results:
@@ -26,47 +24,18 @@ jobs:
           cat combined_test_results.txt
 
       - name: New Failures Introduced
-        id: ci_output
         run: |
           find . -name "new_failures_*.txt" -exec cat {} + > combined_failures.txt
           if [ -s combined_failures.txt ]
           then
               echo "This PR introduces the following new failing tests:"
               cat combined_failures.txt
-              {
-                echo 'MESSAGE<<EOF'
-                echo "# Failed tests:"
-                echo "This PR introduces the following new failing tests:"
-                cat combined_failures.txt
-                echo EOF
-              } >> "$GITHUB_OUTPUT"
           else
-              echo "MESSAGE=This pull request does not result in any additional test failures. Congratulations!" >> "$GITHUB_OUTPUT"
+              echo "This PR does not introduce any new test failures! Yippee!"
           fi
-      - name: Find Comment
-        uses: peter-evans/find-comment@v2
-        id: fc
-        with:
-          issue-number: ${{ github.event.pull_request.number }}
-          comment-author: 'github-actions[bot]'
-          body-includes: <!--- CI Output -->
-
-      - name: Create or update comment
-        uses: peter-evans/create-or-update-comment@v3
-        with:
-          comment-id: ${{ steps.fc.outputs.comment-id }}
-          issue-number: ${{ github.event.pull_request.number }}
-          body: |
-            Thank you for this PR, here is the CI results:
-
-            -------------
-            ${{ steps.ci_output.outputs.MESSAGE}}
-
-            <!--- CI Output -->
-          edit-mode: replace
 
   run_tests:
-    runs-on: ubuntu-latest
+    runs-on: ubuntu-20.04
     strategy:
       fail-fast: false
       matrix:
@@ -93,20 +62,34 @@ jobs:
           submodules: "recursive"
           fetch-depth: 100
 
+      - name: Install ivy and fetch binaries
+        run: |
+          cd ivy
+          pip3 install -e .
+          mkdir .ivy
+          touch .ivy/key.pem
+          echo -n ${{ secrets.USER_API_KEY }} > .ivy/key.pem
+          cd ..
+
+      - name: Get Job URL
+        uses: Tiryoh/gha-jobid-action@v0
+        id: jobs
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          job_name: ${{ github.job }}
+
       - name: Determine and Run Tests
         id: tests
         run: |
-          git clone -b master${{ matrix.branch }} https://github.com/unifyai/Mapping.git --depth 200
+          git clone -b master${{ matrix.branch }} https://github.com/unifyai/Mapping.git --depth 1
           pip install pydriller GitPython
           python ivy/scripts/setup_tests/clone-mapping.py
           cp Mapping/tests.pbz2 ivy/
           cd ivy
-          mkdir .ivy
-          touch .ivy/key.pem
-          echo -n ${{ secrets.USER_API_KEY }} > .ivy/key.pem
           python scripts/determine_tests/determine_tests.py ${{ matrix.branch }} pr
           set -o pipefail
           python scripts/run_tests/run_tests_pr.py new_failures_${{ matrix.branch }}.txt | tee test_results_${{ matrix.branch }}.txt
+          cd ..
         continue-on-error: true
 
       - name: Upload test results

docker/DockerfileGPUMultiCuda → docker/DockerfileGPU

@@ -1,16 +1,32 @@
-# uses the base image which has cuda and cudnn installed(multiple versions) and then installs the
+# installs multiple versions of cuda and cudnn and then installs the
 # latest frameworks and the requirements
-FROM unifyai/multicuda:base
+FROM debian:buster
 WORKDIR /ivy
-ARG fw
 
+# arguments
+ARG fw
 ARG pycon=3.10
 
+# environment variables
 ENV DEBIAN_FRONTEND=noninteractive
-
-# Install miniconda
+ENV TZ=Europe/Moscow
 ENV CONDA_DIR /opt/miniconda/
 
+
+# install base libraries
+RUN grep security /etc/apt/sources.list | tee /etc/apt/security.sources.list && \
+    apt-get update && \
+    apt-get upgrade -o Dir::Etc::SourceList=/etc/apt/security.sources.list -y &&\
+    apt-get -y update && \
+    apt-get install -y gnupg  \
+    curl  \
+    wget  \
+    software-properties-common  \
+    gcc  \
+    nano
+
+
+# install miniconda
 RUN apt clean && \
     rm -rf /var/lib/apt/lists/* && \
     apt-get update && \
@@ -21,10 +37,12 @@ RUN apt clean && \
      /bin/bash ~/miniconda.sh -b -p /opt/miniconda
 
 
+# create conda environment
 ENV PATH=$CONDA_DIR/bin:$PATH
 RUN conda create --name multienv python==$pycon -y
 
-# to fix protobuf conflicts
+
+# fix protobuf conflicts
 ENV PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION python
 ENV PATH=/opt/miniconda/envs/multienv/bin:$PATH
 RUN apt-get update && \
@@ -38,44 +56,42 @@ RUN apt-get update && \
     pip3 install setuptools==58.5.3
 
 
-# Install Ivy Upstream
+# install Ivy Upstream
 RUN git clone --progress --recurse-submodules https://github.com/unifyai/ivy --depth 1 && \
     cd ivy && \
     cd ivy_tests/array_api_testing/test_array_api && \
     pip3 install --no-cache-dir -r requirements.txt
 
-# Install local optional
-COPY /docker/multicuda_framework_directory.py .
+
+# copy library files to workdir
+COPY docker/gpu_framework_directory.py .
 COPY requirements/optional_gpu.txt .
 COPY requirements/requirements.txt .
 
 
-#setting torch path early on because torch-scatter needs it
+# setting torch path early on because torch-scatter needs it
 ENV PYTHONPATH "/opt/fw/torch:/opt/miniconda/envs/multienv/bin"
 
+
 # requirement mappings directs which dependency to be installed and where
 COPY /docker/requirement_mappings_gpu.json .
 SHELL ["/bin/bash", "-c"]
 
 
-
-RUN python3 multicuda_framework_directory.py $fw &&\
+# install all libraries based on the mappings
+RUN python3 gpu_framework_directory.py $fw &&\
     jq -r 'to_entries[] | select(.value != [""]) | .key as $dir | .value[] | @sh "/opt/fw/\($dir) \(.)"' requirement_mappings_gpu.json | xargs -I {} sh -c 'printf "Installing %s\n" $2 && pip install --ignore-installed --target $1 $2 --extra-index-url https://download.pytorch.org/whl/cu118' sh {}
-
-
-
 RUN sed -i '/numpy/d' requirements.txt &&\
     pip install -r  requirements.txt &&\
     cp ./optional_gpu.txt tmp.txt  &&\
     jq -r 'to_entries[] | [.key] + .value | select(length > 0 or (. == "")) | .[]' requirement_mappings_gpu.json | sort -u | xargs -I {} sed -i '/{}/d;/jaxlib/d' tmp.txt && pip install -r tmp.txt
 
 
-
-
 # add all the directories to environment path so that python knows where to find them
 ENV PYTHONPATH "/opt/fw/mxnet:/opt/fw/numpy:/opt/fw/tensorflow:/opt/fw/jax:/opt/fw/torch:/opt/fw/paddle:/opt/miniconda/envs/multienv/bin"
 
 
+# test dependencies
 COPY scripts/test_dependencies.py .
 RUN python3 test_dependencies.py -fp requirements.txt,optional_gpu.txt && \
     rm -rf requirements.txt && \

docker/build_gpu_dockerfile.sh

@@ -0,0 +1 @@
+docker build --progress=plain --no-cache -t unifyai/ivy:latest-gpu  -f DockerfileGPU ..

docker/rebuild_all_dockerfiles.sh

@@ -1,4 +1,4 @@
 #!/bin/bash
 
 docker build -t unifyai/ivy:latest --no-cache -f Dockerfile ..
-docker build -t unifyai/multicuda:base_and_requirements --no-cache -f DockerfileGPUMultiCuda ..
+docker build -t unifyai/ivy:latest-gpu --no-cache -f DockerfileGPU ..

docs/overview/contributing/setting_up.rst

@@ -715,7 +715,7 @@ Just follow the steps outlined below:
 
       - :code:`Default project configuration` - This is the default option, it will set up with the default codespaces environment.
       - :code:`Ivy Development Environment (build)` - This will set up the development environment of ivy for CPU and build image from :code:`ivy/docker/Dockerfile`.
-      - :code:`Ivy GPU Development Environment (build)` - This will set up the development environment of ivy for GPU and build image from :code:`ivy/docker/DockerfileGPUMultiCuda`.
+      - :code:`Ivy GPU Development Environment (build)` - This will set up the development environment of ivy for GPU and build image from :code:`ivy/docker/DockerfileGPU`.
       - :code:`Ivv Development Environment for Multiver...` - This will set up the development environment of multiversion support with ivy and build image from :code:`ivy/docker/DockerfileMultiversion`.
       - :code:`Ivy Development Environment (image)` - This will set up the development environment of ivy for CPU and build image from the latest image from dockerhub.
       - :code:`Ivy GPU Development Environment (image)` - This will set up the development environment of ivy for GPU and build image from the latest image from dockerhub.

ivy/functional/backends/jax/experimental/layers.py

@@ -149,7 +149,7 @@ def general_pool(
         # if dtype is not set here, jax casts it to float64
         inputs = jnp.array(inputs, dtype=jnp.float32)
     if not ivy.is_array(init):
-        init = jnp.array(init, dtype=jnp.float32)
+        init = jnp.array(init, dtype=inputs.dtype)
     promoted_type = jnp.promote_types(inputs.dtype, init.dtype)
     inputs = inputs.astype(promoted_type)
     init = init.astype(promoted_type)
@@ -703,7 +703,7 @@ def interpolate(
     out: Optional[JaxArray] = None,
 ):
     dims = len(x.shape) - 2
-    size = _get_size(scale_factor, size, dims, x.shape)
+    size, _ = _get_size(scale_factor, size, dims, x.shape)
     mode = (
         "nearest"
         if mode == "nearest-exact"

ivy/functional/backends/tensorflow/experimental/layers.py

@@ -893,7 +893,7 @@ def interpolate(
     out: Optional[Union[tf.Tensor, tf.Variable]] = None,
 ):
     dims = len(x.shape) - 2
-    size = _get_size(scale_factor, size, dims, x.shape)
+    size, _ = _get_size(scale_factor, size, dims, x.shape)
     remove_dim = False
     if mode in ["linear", "tf_area", "lanczos3", "lanczos5", "nearest-exact"]:
         if dims == 1:

ivy/functional/frontends/torch/nn/functional/pooling_functions.py

@@ -114,6 +114,10 @@ def avg_pool1d(
     )
 
 
+@with_unsupported_dtypes(
+    {"2.1.0 and below": ("float16",)},
+    "torch",
+)
 @to_ivy_arrays_and_back
 def avg_pool2d(
     input,

ivy/functional/frontends/torch/reduction_ops.py

@@ -162,6 +162,10 @@ def median(input, dim=None, keepdim=False, *, out=None):
 
 @numpy_to_torch_style_args
 @to_ivy_arrays_and_back
+@with_unsupported_dtypes(
+    {"2.1.0 and below": ("complex64", "complex128")},
+    "torch",
+)
 def min(*input, dim=None, keepdim=False, out=None):
     if len(input) == 1:
         input = input[0]