[ impl ] Flexible Matching evaluation

.gitignore

@@ -1,7 +1,3 @@
 __pycache__
-*.json
-!configs/*.json
-*.relay
-!tests/models
-tests/params/
-.pkl_memoize_py3
+.pkl_memoize_py3
+tests/data

README.md

@@ -17,4 +17,27 @@ Flexible Matching via Equality Saturation
     - Takes the **relay source file**, the output model and eclass analysis data json from EqSat
     - Compiles the rewritten model back to a relay executable model and saves to a file
     - Optional argument: `--debug`; instead of inserting accelerator calls, if this argument is passed, the equivalent relay function will be generated
-    - Example: `python3 compile_model.py models/resmlp.relay resmlp-rewritten.relay resmlp-rewritten.json resmlp-data.json linear-rewrites im2col-rewrites --debug`
+    - Example: `python3 compile_model.py models/resmlp.relay resmlp-rewritten.relay resmlp-rewritten.json resmlp-data.json linear-rewrites im2col-rewrites --debug`
+
+# End-to-end compilation validation
+```bash
+python3 validate_compilation.py model ([--configs CONFIGS+] | [--defaults]) [--use-ilp] [--debug]
+```
+- `model`: resnet18; efficientnet; max_pool2d; mobilenet; resmlp
+- `configs`: hlscnn-conv2d; flexasr-maxpool; im2col; vta-dense; linear-rewrites
+    - hlscnn-conv2d: `Conv2D` to HLSCNN
+    - flexasr-maxpool: `Max_pool2D` to FlexASR
+    - im2col: Convolutions to matmuls
+    - linear-rewrites: `nn.Linear` to FlexASR
+- `--defaults`: if turned oon, use default configs
+- `--use-ilp`: Use CPLEX ILP Solver to extract the rewritten model
+- `--debug`: Use debug functions to replace accelerator calls for debug purposes
+
+Example: `python3 validate_compilation.py resnet18 --configs im2col vta-dense --debug`
+
+# Rewrite Config Structure
+- rewrites :: `Dict[String, Array[Integer]]`. rewrite rules to apply
+- composites :: `Dict[String (accelerator func names), String]`. Compiler composite region annotations
+- compiler :: `Dict[String (accelerator func names), String]`. which compiler to use
+- debug_functions :: `Dict[String (accelerator func names), String]`. debug functions for corresponding accelerator calls
+- out_dtypes :: `Dict[String (accelerator func names), String (dtype names)]`. Output data type of the accelerator function.

configs/flexasr-lstm.json

@@ -0,0 +1,17 @@
+{
+    "rewrites": {
+        "flex-lstm": []
+    },
+    "composites": {
+        "flex-lstm": "ilaflex.lstm"
+    },
+    "compilers": {
+        "flex-lstm": "ilaflex"
+    },
+    "debug_functions": {
+        "flex-lstm": "lambda *inputs: tvm.parser.fromtext(open('./models/lstm-for-pldi-pattern.relay').read())['main'](*inputs)"
+    },
+    "out_dtypes": {
+        "flex-lstm": "float32"
+    }
+}

configs/flexasr-maxpool.json

@@ -11,12 +11,15 @@
         "simplify-reduce-max": []
     },
     "composites": {
-        "flexasr-maxpool": "ilaflex.max_pool"
+        "flex-maxpool": "ilaflex.max_pool"
     },
     "compilers": {
-        "flexasr-maxpool": "ilaflex"
+        "flex-maxpool": "ilaflex"
     },
     "debug_functions": {
-        "flexasr-maxpool": "nn.max_pool2d"
+        "flex-maxpool": "lambda x: relay.expand_dims(relay.max(x, axis=0), axis=0)"
+    },
+    "out_dtypes": {
+        "flex-maxpool": "float32"
     }
 }

configs/hlscnn-conv2d.json

@@ -9,6 +9,9 @@
         "hlscnn-conv2d": "ilacnn"
     },
     "debug_functions": {
-        "hlscnn-conv2d": "nn.conv2d"
+        "hlscnn-conv2d": "RelayOperators.RelayConv2D"
+    },
+    "out_dtypes": {
+        "hlscnn-conv2d": "float32"
     }
 }

configs/im2col.json

@@ -0,0 +1,12 @@
+{
+    "rewrites": {
+        "flatten-unflatten-all-accesses": [],
+        "bubble-reshape-through-cartesian-product": [],
+        "bubble-reshape-through-compute-dot-product": [],
+        "access-reshape-to-relay": []
+    },
+    "composites": {},
+    "compilers": {},
+    "debug_functions": {},
+    "out_dtypes": {}
+}

configs/linear-rewrites.json

@@ -2,7 +2,9 @@
     "rewrites": {
         "linear-rewrites": [],
         "access-reshape-to-relay": [],
-        "flex-linear-rewrite": []
+        "flex-linear-rewrite": [],
+        "add_bias_add_to_dense": [],
+        "glenside_matmul_to_relay_dense": []
     },
     "composites": {
         "flex-linear": "ilaflex.linear"
@@ -12,5 +14,8 @@
     },
     "debug_functions": {
         "flex-linear": "lambda x, w, b: nn.bias_add(nn.dense(x, w), b)"
+    },
+    "out_dtypes": {
+        "flex-linear": "float32"
     }
 }

configs/qnn-vta-dense.json

@@ -0,0 +1,17 @@
+{
+    "rewrites": {
+        "vta-dense-rewrite": []
+    },
+    "composites": {
+        "vta-dense": "ilavta.dense"
+    },
+    "compilers": {
+        "vta-dense": "ilavata"
+    },
+    "debug_functions": {
+        "vta-dense": "lambda x,w: nn.dense(x, w, out_dtype='int32')"
+    },
+    "out_dtypes": {
+        "vta-dense": "int32"
+    }
+}

configs/im2col-rewrites.json → configs/vta-dense.json

@@ -1,9 +1,5 @@
 {
     "rewrites": {
-        "flatten-unflatten-all-accesses": [],
-        "bubble-reshape-through-cartesian-product": [],
-        "bubble-reshape-through-compute-dot-product": [],
-        "access-reshape-to-relay": [],
         "vta-dense-rewrite": []
     },
     "composites": {
@@ -14,5 +10,8 @@
     },
     "debug_functions": {
         "vta-dense": "nn.dense"
+    },
+    "out_dtypes": {
+        "vta-dense": "float32"
     }
 }