[GitHub] [tvm] Hzfengsy commented on a change in pull request #7831: [AutoTVM] [TOPI] Support AutoTVM for int4 tensorcore

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

Hzfengsy commented on a change in pull request #7831:
URL: https://github.com/apache/tvm/pull/7831#discussion_r612058941



##########
File path: python/tvm/topi/cuda/conv2d_hwnc_tensorcore.py
##########
@@ -254,13 +253,8 @@ def schedule_hwnc_tensorcore_cuda(cfg, s, Conv):
     vector_as = cfg["vector_as"].val
     vector_ws = cfg["vector_ws"].val
     split_block_k_nums = cfg["split_block_k_nums"].val
-    fuse_pack = cfg["fuse_pack"].val
 
-    if not fuse_pack:
-        s[packed_data].compute_inline()
-    else:
-        with Target("cuda"):
-            schedule_injective_from_existing(s, packed_data)
+    s[packed_data].compute_inline()

Review comment:
       Please show why narrowing search space

##########
File path: src/runtime/contrib/random/mt_random_engine.cc
##########
@@ -134,12 +134,16 @@ class RandomEngine {
 
  private:
   void FillData(DLTensor* tensor, int64_t size) {
-    // Make the value be 1.0 - 10.0, not (0.0 - 1.0) so that we could satisfy
+    // Make the value be 17.0 - 30.0, not (0.0 - 1.0) so that we could satisfy
     // quantized dtype (uint8 / int8) data non-empty requirement
-    std::uniform_real_distribution<> dist(1.0, 10.0);
+    // We start from 17.0 because two int4 are packed in a single uint8
+    std::uniform_real_distribution<> dist(17.0, 30.0);

Review comment:
       Why 17.0-30.0?




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