notebooks: rerun notebooks. (#1026)

Xilinx · Sep 12, 2024 · 86afd5f · 86afd5f
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Showing 7 changed files with 176 additions and 161 deletions.
diff --git a/notebooks/01_quant_tensor_quant_conv2d_overview.ipynb b/notebooks/01_quant_tensor_quant_conv2d_overview.ipynb
diff --git a/notebooks/02_quant_activation_overview.ipynb b/notebooks/02_quant_activation_overview.ipynb
diff --git a/notebooks/03_anatomy_of_a_quantizer.ipynb b/notebooks/03_anatomy_of_a_quantizer.ipynb
diff --git a/notebooks/Brevitas_TVMCon2021.ipynb b/notebooks/Brevitas_TVMCon2021.ipynb
diff --git a/notebooks/ONNX_export_tutorial.ipynb b/notebooks/ONNX_export_tutorial.ipynb
@@ -32,7 +32,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Requirement already satisfied: netron in /scratch/fabian/miniforge3/envs/torchgpu/lib/python3.11/site-packages (7.4.5)\n",
+      "Requirement already satisfied: netron in /proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages (7.2.9)\r\n",
       "Note: you may need to restart the kernel to use updated packages.\n"
      ]
     }
@@ -555,7 +555,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-03-06 02:12:47.492497092 [W:onnxruntime:, graph.cc:1283 Graph] Initializer linear.bias appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.\n"
+      "2024-09-12 12:18:03.405472924 [W:onnxruntime:, graph.cc:1283 Graph] Initializer linear.bias appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/nn/quant_linear.py:69: UserWarning: Defining your `__torch_function__` as a plain method is deprecated and will be an error in future, please define it as a classmethod. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525541990/work/torch/csrc/utils/python_arg_parser.cpp:350.)\n",
+      "  output_tensor = linear(x, quant_weight, quant_bias)\n"
      ]
     }
    ],
@@ -771,7 +773,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.10.13"
   },
   "vscode": {
    "interpreter": {

diff --git a/notebooks/minifloat_mx_tutorial.ipynb b/notebooks/minifloat_mx_tutorial.ipynb
@@ -67,7 +67,10 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/giuseppe/miniconda3/envs/brevitas_dev/lib/python3.11/site-packages/torch/nn/modules/conv.py:456: UserWarning: Defining your `__torch_function__` as a plain method is deprecated and will be an error in future, please define it as a classmethod. (Triggered internally at /opt/conda/conda-bld/pytorch_1712608853099/work/torch/csrc/utils/python_arg_parser.cpp:294.)\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/torch/_tensor.py:1255: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525541990/work/c10/core/TensorImpl.h:1758.)\n",
+      "  return super(Tensor, self).rename(names)\n",
+      "[W NNPACK.cpp:53] Could not initialize NNPACK! Reason: Unsupported hardware.\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/torch/nn/modules/conv.py:459: UserWarning: Defining your `__torch_function__` as a plain method is deprecated and will be an error in future, please define it as a classmethod. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525541990/work/torch/csrc/utils/python_arg_parser.cpp:350.)\n",
       "  return F.conv2d(input, weight, bias, self.stride,\n"
      ]
     }
@@ -152,7 +155,16 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/quant/solver/act.py:132: UserWarning: Group dim is being selected assuming batched input. Using unbatched input will fail and requires manually specification of group_dim\n",
+      "  warn(\n"
+     ]
+    }
+   ],
    "source": [
     "from brevitas.quant_tensor import GroupwiseFloatQuantTensor\n",
     "\n",
@@ -204,14 +216,6 @@
       "Non padding weights shape torch.Size([64, 8, 3, 3])\n",
       "Padded weights shape torch.Size([64, 32, 3, 3])\n"
      ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/giuseppe/miniconda3/envs/brevitas_dev/lib/python3.11/site-packages/torch/nn/modules/conv.py:456: UserWarning: Defining your `__torch_function__` as a plain method is deprecated and will be an error in future, please define it as a classmethod. (Triggered internally at /opt/conda/conda-bld/pytorch_1712608853099/work/torch/csrc/utils/python_arg_parser.cpp:294.)\n",
-      "  return F.conv2d(input, weight, bias, self.stride,\n"
-     ]
     }
    ],
    "source": [
@@ -353,7 +357,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,

diff --git a/notebooks/quantized_recurrent.ipynb b/notebooks/quantized_recurrent.ipynb
@@ -116,7 +116,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/scratch/fabian/brevitas/src/brevitas/nn/mixin/base.py:78: UserWarning: Keyword arguments are being passed but they not being used.\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/nn/mixin/base.py:55: UserWarning: Keyword arguments are being passed but they not being used.\n",
       "  warn('Keyword arguments are being passed but they not being used.')\n"
      ]
     }
@@ -384,14 +384,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/scratch/fabian/brevitas/src/brevitas/nn/mixin/base.py:307: UserWarning: Defining your `__torch_function__` as a plain method is deprecated and will be an error in future, please define it as a classmethod. (Triggered internally at /opt/conda/conda-bld/pytorch_1699449183005/work/torch/csrc/utils/python_arg_parser.cpp:368.)\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/nn/mixin/base.py:216: UserWarning: Defining your `__torch_function__` as a plain method is deprecated and will be an error in future, please define it as a classmethod. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525541990/work/torch/csrc/utils/python_arg_parser.cpp:350.)\n",
       "  return torch.cat(outputs, dim=seq_dim)\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "(QuantTensor(value=tensor([[[-0.0062, -0.2872,  0.7931,  0.4309,  0.5495, -0.4558,  0.2373,\n",
+       "(IntQuantTensor(value=tensor([[[-0.0062, -0.2872,  0.7931,  0.4309,  0.5495, -0.4558,  0.2373,\n",
        "            0.6807,  0.4621,  0.6120, -0.1124,  0.3872,  0.3060,  0.7681,\n",
        "           -0.3684,  0.0437, -0.7369, -0.3247,  0.7743,  0.3372],\n",
        "          [ 0.5450,  0.2962, -0.3969,  0.3555, -0.5628,  0.2429, -0.4976,\n",
@@ -423,7 +423,7 @@
        "           -0.2664,  0.4923,  0.2143, -0.4170,  0.4112,  0.5502,  0.7066,\n",
        "           -0.6024,  0.7356,  0.0348,  0.1043, -0.1911, -0.4518]]],\n",
        "        grad_fn=<CatBackward0>), scale=tensor(0.0059, grad_fn=<DivBackward0>), zero_point=tensor(0.), bit_width=tensor(8.), signed_t=tensor(True), training_t=tensor(True)),\n",
-       " QuantTensor(value=tensor([[[ 0.0579, -0.0058, -0.4054, -0.1564, -0.5560, -0.3301,  0.3533,\n",
+       " IntQuantTensor(value=tensor([[[ 0.0579, -0.0058, -0.4054, -0.1564, -0.5560, -0.3301,  0.3533,\n",
        "            0.0058, -0.1622, -0.3765,  0.1216,  0.0695, -0.4054,  0.0927,\n",
        "            0.6139, -0.1390,  0.7066,  0.1274,  0.1622, -0.2896],\n",
        "          [-0.0290, -0.1738,  0.0695,  0.3765,  0.1738,  0.0579, -0.4054,\n",
@@ -462,14 +462,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/scratch/fabian/miniforge3/envs/torchgpu/lib/python3.11/site-packages/torch/_tensor.py:1362: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /opt/conda/conda-bld/pytorch_1699449183005/work/c10/core/TensorImpl.h:1900.)\n",
-      "  return super().rename(names)\n"
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/torch/_tensor.py:1255: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525541990/work/c10/core/TensorImpl.h:1758.)\n",
+      "  return super(Tensor, self).rename(names)\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "(QuantTensor(value=tensor([[[ 0.2111,  0.1267,  0.0060,  0.6153, -0.7721, -0.3740, -0.5188,\n",
+       "(IntQuantTensor(value=tensor([[[ 0.2111,  0.1267,  0.0060,  0.6153, -0.7721, -0.3740, -0.5188,\n",
        "            0.6273,  0.4162,  0.2051,  0.2292,  0.7239,  0.6032,  0.2533,\n",
        "            0.5067,  0.6635,  0.1206, -0.5730,  0.0483,  0.3318],\n",
        "          [ 0.5742,  0.0194, -0.3807, -0.0710, -0.6000,  0.1807,  0.1355,\n",
@@ -501,7 +501,7 @@
        "            0.4136,  0.5383, -0.3085,  0.4070,  0.4070,  0.6630, -0.0263,\n",
        "            0.2823, -0.1510,  0.1313, -0.5186,  0.4464, -0.0066]]],\n",
        "        grad_fn=<CatBackward0>), scale=tensor(0.0062, grad_fn=<DivBackward0>), zero_point=tensor(0.), bit_width=tensor(8.), signed_t=tensor(True), training_t=tensor(True)),\n",
-       " QuantTensor(value=tensor([[[ 0.0000, -0.4004,  0.3151, -0.0263, -0.5842, -0.1641, -0.3939,\n",
+       " IntQuantTensor(value=tensor([[[ 0.0000, -0.4004,  0.3151, -0.0263, -0.5842, -0.1641, -0.3939,\n",
        "            0.0263, -0.2429,  0.6499, -0.5186,  0.1247, -0.2101,  0.8337,\n",
        "           -0.1444,  0.6762, -0.1641, -0.5317, -0.1707, -0.0197],\n",
        "          [ 0.3479,  0.5974, -0.3939,  0.1444, -0.6762,  0.1969, -0.6499,\n",
@@ -538,7 +538,7 @@
     {
      "data": {
       "text/plain": [
-       "(QuantTensor(value=tensor([[[-0.3777, -0.2074,  0.7184,  0.9110,  0.0148, -0.1926, -0.7110,\n",
+       "(IntQuantTensor(value=tensor([[[-0.3777, -0.2074,  0.7184,  0.9110,  0.0148, -0.1926, -0.7110,\n",
        "            0.1926, -0.4222, -0.9480,  0.2592,  0.2222, -0.2370, -0.5407,\n",
        "            0.5851, -0.2370,  0.3555,  0.1703,  0.4444, -0.2222],\n",
        "          [ 0.4814, -0.7355, -0.1605,  0.3878, -0.5282,  0.2073,  0.0000,\n",
@@ -570,7 +570,7 @@
        "           -0.3422,  0.8028,  0.0855, -0.7238, -0.6317,  0.2764, -0.0461,\n",
        "           -0.4211, -0.5988,  0.2632,  0.4014, -0.7501, -0.5659]]],\n",
        "        grad_fn=<CatBackward0>), scale=tensor(0.0069, grad_fn=<DivBackward0>), zero_point=tensor(0.), bit_width=tensor(8.), signed_t=tensor(True), training_t=tensor(True)),\n",
-       " QuantTensor(value=tensor([[[-0.0066,  0.4804,  0.0066, -0.1184,  0.6843, -0.0197,  0.1448,\n",
+       " IntQuantTensor(value=tensor([[[-0.0066,  0.4804,  0.0066, -0.1184,  0.6843, -0.0197,  0.1448,\n",
        "            0.1842,  0.6383, -0.1908, -0.0066, -0.1053, -0.1316,  0.0461,\n",
        "           -0.0066, -0.2764,  0.3751,  0.3619,  0.5001, -0.1316],\n",
        "          [-0.6449,  0.5856, -0.0263, -0.0197,  0.8357, -0.5856,  0.0395,\n",
@@ -985,7 +985,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-02-28 05:30:11.212034979 [W:onnxruntime:, graph.cc:1283 Graph] Initializer onnx::LSTM_93 appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.\n"
+      "2024-09-12 12:18:52.692518968 [W:onnxruntime:, graph.cc:1283 Graph] Initializer onnx::LSTM_93 appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.\n"
      ]
     }
    ],
@@ -1084,7 +1084,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-02-28 05:30:18.857576114 [W:onnxruntime:, graph.cc:1283 Graph] Initializer onnx::LSTM_87 appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.\n"
+      "2024-09-12 12:18:53.086326293 [W:onnxruntime:, graph.cc:1283 Graph] Initializer onnx::LSTM_87 appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.\n"
      ]
     }
    ],
@@ -1115,7 +1115,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/scratch/fabian/brevitas/src/brevitas/nn/mixin/base.py:78: UserWarning: Keyword arguments are being passed but they not being used.\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/nn/mixin/base.py:55: UserWarning: Keyword arguments are being passed but they not being used.\n",
       "  warn('Keyword arguments are being passed but they not being used.')\n"
      ]
     }
@@ -1191,7 +1191,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/scratch/fabian/brevitas/src/brevitas/nn/mixin/base.py:78: UserWarning: Keyword arguments are being passed but they not being used.\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/nn/mixin/base.py:55: UserWarning: Keyword arguments are being passed but they not being used.\n",
       "  warn('Keyword arguments are being passed but they not being used.')\n"
      ]
     }
@@ -1268,7 +1268,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/scratch/fabian/brevitas/src/brevitas/nn/mixin/base.py:78: UserWarning: Keyword arguments are being passed but they not being used.\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/nn/mixin/base.py:55: UserWarning: Keyword arguments are being passed but they not being used.\n",
       "  warn('Keyword arguments are being passed but they not being used.')\n"
      ]
     }
@@ -1345,7 +1345,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/scratch/fabian/brevitas/src/brevitas/nn/mixin/base.py:78: UserWarning: Keyword arguments are being passed but they not being used.\n",
+      "/proj/xlabs/users/nfraser/opt/miniforge3/envs/20231115_brv_pt1.13.1/lib/python3.10/site-packages/brevitas/nn/mixin/base.py:55: UserWarning: Keyword arguments are being passed but they not being used.\n",
       "  warn('Keyword arguments are being passed but they not being used.')\n"
      ]
     }
@@ -1420,17 +1420,7 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "[W shape_type_inference.cpp:1974] Warning: The shape inference of onnx.brevitas::QuantLSTMCell type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function. (function UpdateReliable)\n",
-      "[W shape_type_inference.cpp:1974] Warning: The shape inference of onnx.brevitas::QuantLSTMCell type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function. (function UpdateReliable)\n",
-      "[W shape_type_inference.cpp:1974] Warning: The shape inference of onnx.brevitas::QuantLSTMCell type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function. (function UpdateReliable)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import torch\n",
     "from brevitas.nn import QuantLSTM\n",
@@ -1566,7 +1556,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.10.13"
   },
   "vscode": {
    "interpreter": {