[GitHub] [tvm] ekalda commented on a change in pull request #9626: [microNPU] Support different constant datatypes

[GitBox <gi...@apache.org>]

ekalda commented on a change in pull request #9626:
URL: https://github.com/apache/tvm/pull/9626#discussion_r761199497



##########
File path: python/tvm/relay/backend/contrib/ethosu/legalize.py
##########
@@ -1156,6 +1156,7 @@ def transform_module(
         mod = LegalizeReshape()(mod)
         mod = LegalizeStridedSlice()(mod)
         mod = LegalizeNoOps()(mod)
+        print(mod)

Review comment:
       Nit: remove the print

##########
File path: python/tvm/relay/backend/contrib/ethosu/legalize.py
##########
@@ -1040,7 +1040,7 @@ def callback(
             n = int(filter_height * filter_width)
             eps = 1 / (256 * (n + 1)) if n % 2 == 0 else 0
 
-            scalar_tensor = relay.const(np.ones([1, 1, 1, 1], dtype="uint8"), dtype="uint8")
+            scalar_tensor = relay.const(np.ones([1, 1, 1, 1], dtype="int16"), dtype="int16")

Review comment:
       For enlightenment, why `int16` (as opposed to e.g. `int32`)?

##########
File path: python/tvm/relay/backend/contrib/ethosu/tir_to_cs_translator.py
##########
@@ -277,27 +276,24 @@ def classify_io(buffer):
         raise ValueError(f"Unused IO : {buffer} in tir module.")
 
     scratch_size = 0
-    constant_tensor = None
+    constant_hex_data = []
+    total_constant_len = 0
     buffer_addresses = dict()
     for _buffer, info in buffer_info.items():
         if info.values is not None:
-            assert np.dtype(info.dtype) == np.uint8
             assert info.btype == BufferType.constant
             assert len(info.shape) == 1
-            if constant_tensor is None:
-                buffer_addresses[_buffer] = (0, info.btype)
-                assert info.values.dtype == np.uint8
-                size_in_bytes = info.values.size
-                # Every memory address the NPU access have to be 16 byte aligned
-                size_in_bytes = util.round_up(size_in_bytes, 16)
-                constant_tensor = np.resize(info.values, size_in_bytes)
-            else:
-                buffer_addresses[_buffer] = (constant_tensor.size, info.btype)
-                assert info.values.dtype == np.uint8
-                size_in_bytes = info.values.size
-                # Every memory address the NPU access have to be 16 byte aligned
-                size_in_bytes = util.round_up(size_in_bytes, 16)
-                constant_tensor = np.append(constant_tensor, np.resize(info.values, size_in_bytes))
+            buffer_addresses[_buffer] = (
+                (total_constant_len, info.btype) if constant_hex_data else (0, info.btype)
+            )
+            dtype_bytes = np.iinfo(np.dtype(info.dtype)).bits // 8
+            size_in_bytes = dtype_bytes * np.prod(list(info.shape))
+            # Every memory address the NPU access have to be 16 byte aligned
+            size_in_bytes = util.round_up(size_in_bytes, 16)
+            constant_tensor = np.resize(info.values, size_in_bytes // dtype_bytes)
+            constant_tensor = constant_tensor.tobytes().hex()
+            constant_hex_data.append(constant_tensor)
+            total_constant_len += len(constant_tensor) // 2

Review comment:
       For enlightenment, why division by 2?




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