fix: got the tests passing for all the demos except 02_unify_code, mm…

…pretrain and xgboost
ivy-llc · Nov 3, 2023 · 4dd0dc9 · 4dd0dc9
1 parent a1c686a
commit 4dd0dc9
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Showing 9 changed files with 118,177 additions and 133 deletions.
diff --git a/data/train.csv b/data/train.csv
diff --git a/examples_and_demos/resnet_demo.ipynb b/examples_and_demos/resnet_demo.ipynb
diff --git a/examples_and_demos/torch_to_jax.ipynb b/examples_and_demos/torch_to_jax.ipynb
@@ -33,11 +33,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 1,
       "metadata": {
         "id": "nnyOp6JusBLv"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+            "\u001b[0m"
+          ]
+        }
+      ],
       "source": [
         "!pip install -q ivy\n",
         "!pip install -q transformers\n",
@@ -82,11 +93,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 3,
       "metadata": {
         "id": "Fl2RJ_KlsNy2"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "2023-11-02 19:23:15.980130: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+            "2023-11-02 19:23:15.980177: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+            "2023-11-02 19:23:15.980207: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+            "2023-11-02 19:23:17.351203: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+          ]
+        }
+      ],
       "source": [
         "jax.config.update(\"jax_enable_x64\", False)\n",
         "\n",
@@ -132,15 +154,26 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 5,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "DEBx4fwFvmC-",
         "outputId": "ef553432-e143-4248-c674-d0c0a6bf80db"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "WARNING:root:To preserve the tracer and transpiler caches across multiple machines, ensure that the relative path of your projects from the .ivy folder is consistent across all machines. You can do this by adding .ivy to your home folder and placing all projects in the same place relative to the home folder on all machines.\n",
+            "WARNING:root:Native Numpy does not support GPU placement, consider using Jax instead\n",
+            "/workspaces/ivy/ivy/utils/exceptions.py:390: UserWarning: The current backend: 'jax' does not support inplace updates natively. Ivy would quietly create new arrays when using inplace updates with this backend, leading to memory overhead (same applies for views). If you want to control your memory management, consider doing ivy.set_inplace_mode('strict') which should raise an error whenever an inplace update is attempted with this backend.\n",
+            "  warnings.warn(\n"
+          ]
+        }
+      ],
       "source": [
         "transpiled_graph = ivy.transpile(model, to=\"haiku\", kwargs=inputs)"
       ]
@@ -217,7 +250,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 15,
+      "execution_count": 8,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -230,7 +263,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "9.67 ms ± 2.28 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+            "6.63 ms ± 122 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
           ]
         }
       ],
@@ -241,7 +274,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 16,
+      "execution_count": 9,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -254,7 +287,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "4.09 ms ± 9.48 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+            "1.18 ms ± 134 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
           ]
         }
       ],
@@ -340,7 +373,8 @@
       "name": "python3"
     },
     "language_info": {
-      "name": "python"
+      "name": "python",
+      "version": "3.10.0"
     }
   },
   "nbformat": 4,