Updated notebooks

notebooks/minifloat_mx_tutorial.ipynb

@@ -163,8 +163,8 @@
     "    pass\n",
     "\n",
     "class MXFloat8Act(MXFloat8e4m3Act, Fp8e4m3Mixin):\n",
-    "    # It is necessary to specify the group dimension for the activation quantization\n",
-    "    group_dim = 1\n",
+    "    # In layerwise quantization, groupdim is automatically determined\n",
+    "    pass\n",
     "\n",
     "\n",
     "class MXModel(nn.Module):\n",
@@ -221,9 +221,8 @@
     "    group_size = 8\n",
     "\n",
     "class MXFloat8ActNoPadding(MXFloat8e4m3Act, Fp8e4m3Mixin):\n",
-    "    # It is necessary to specify the group dimension for the activation quantization\n",
+    "    # In layerwise quantization, groupdim is automatically determined\n",
     "    group_size = 8\n",
-    "    group_dim = 1\n",
     "\n",
     "\n",
     "class MXModelNoPadding(nn.Module):\n",
@@ -277,8 +276,8 @@
     "    pass\n",
     "\n",
     "class MXFloat8Act(MXFloat8e4m3Act, Fp8e4m3Mixin):\n",
-    "    # It is necessary to specify the group dimension for the activation quantization\n",
-    "    group_dim = 1\n",
+    "    # In layerwise quantization, groupdim is automatically determined\n",
+    "    pass\n",
     "\n",
     "\n",
     "class MXModel(nn.Module):\n",
@@ -314,12 +313,11 @@
     "class MXInt8Weight(MXInt8Weight):\n",
     "    # The group dimension for the weights it is automatically identified based on the layer type\n",
     "    # If a new layer type is used, it can be manually specified\n",
-    "    bit_width = 8\n",
+    "    pass\n",
     "\n",
     "class MXInt8Act(MXInt8Act):\n",
-    "    # It is necessary to specify the group dimension for the activation quantization\n",
-    "    group_dim = 1\n",
-    "    bit_width = 8\n",
+    "    # In layerwise quantization, groupdim is automatically determined\n",
+    "    pass\n",
     "\n",
     "class MXModel(nn.Module):\n",
     "    def __init__(self):\n",