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Fix: Correct Relax API usage for Var creation and module building #38

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Fix: Correct Relax API usage for Var creation and module building #38

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8 changes: 4 additions & 4 deletions assignment/assignment1.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -206,7 +206,7 @@
"\n",
"def emit_te_example():\n",
" bb = relax.BlockBuilder()\n",
" x = relax.Var(\"x\", (128, 128), relax.DynTensorType(2, \"float32\"))\n",
" x = relax.Var(\"x\", relax.TensorStructInfo((128, 128), \"float32\"))\n",
" with bb.function(\"main\", [x]):\n",
" with bb.dataflow():\n",
" lv0 = bb.emit_te(relu, x)\n",
Expand Down Expand Up @@ -253,7 +253,7 @@
"source": [
"def create_model_via_emit_te():\n",
" bb = relax.BlockBuilder()\n",
" x = relax.Var(\"x\", input_shape, relax.DynTensorType(batch_size, \"float32\"))\n",
" x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
"\n",
" conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
" conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",
Expand All @@ -272,7 +272,7 @@
"\n",
"\n",
"def build_mod(mod):\n",
" exec = relax.vm.build(mod, \"llvm\")\n",
" exec = relax.build(mod, \"llvm\")\n",
" dev = tvm.cpu()\n",
" vm = relax.VirtualMachine(exec, dev)\n",
" return vm\n",
Expand Down Expand Up @@ -362,7 +362,7 @@
"def create_model_with_torch_func():\n",
" bb = relax.BlockBuilder()\n",
"\n",
" x = relax.Var(\"x\", input_shape, relax.DynTensorType(4, \"float32\"))\n",
" x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
"\n",
" conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
" conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",
Expand Down
8 changes: 4 additions & 4 deletions assignment/assignment1_zh.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -205,7 +205,7 @@
"\n",
"def emit_te_example():\n",
" bb = relax.BlockBuilder()\n",
" x = relax.Var(\"x\", (128, 128), relax.DynTensorType(2, \"float32\"))\n",
" x = relax.Var(\"x\", relax.TensorStructInfo((128, 128), \"float32\"))\n",
" with bb.function(\"main\", [x]):\n",
" with bb.dataflow():\n",
" lv0 = bb.emit_te(relu, x)\n",
Expand Down Expand Up @@ -252,7 +252,7 @@
"source": [
"def create_model_via_emit_te():\n",
" bb = relax.BlockBuilder()\n",
" x = relax.Var(\"x\", input_shape, relax.DynTensorType(batch_size, \"float32\"))\n",
" x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
"\n",
" conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
" conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",
Expand All @@ -271,7 +271,7 @@
"\n",
"\n",
"def build_mod(mod):\n",
" exec = relax.vm.build(mod, \"llvm\")\n",
" exec = relax.build(mod, \"llvm\")\n",
" dev = tvm.cpu()\n",
" vm = relax.VirtualMachine(exec, dev)\n",
" return vm\n",
Expand Down Expand Up @@ -362,7 +362,7 @@
"def create_model_with_torch_func():\n",
" bb = relax.BlockBuilder()\n",
"\n",
" x = relax.Var(\"x\", input_shape, relax.DynTensorType(4, \"float32\"))\n",
" x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
"\n",
" conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
" conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",
Expand Down