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apache · Mar 30, 2021 · e2b5c1a · e2b5c1a
2 parents fdfb93a + 9b43a64
commit e2b5c1a
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Showing 7 changed files with 23 additions and 9 deletions.
diff --git a/tests/python/contrib/test_miopen.py b/tests/python/contrib/test_miopen.py
@@ -63,11 +63,11 @@ def verify():
             X, W, (stride_h, stride_w), (pad_h, pad_w), (dilation_h, dilation_w)
         )
         s_ref = te.create_schedule(Y_ref.op)
+<<<<<<< HEAD
         f_ref = tvm.build(s_ref, [X, W, Y_ref], "rocm --host=llvm")
+=======
+        f_ref = tvm.build(s_ref, [X, W, Y_ref], "rocm", target_host="llvm")
         y_ref = tvm.nd.array(np.random.uniform(-1, 1, yshape).astype(np.float32), dev)
-        f_ref(x, w, y_ref)
-        print("Max abs diff:", np.max(np.abs(y.asnumpy() - y_ref.asnumpy())))
-        tvm.testing.assert_allclose(y.asnumpy(), y_ref.asnumpy(), atol=1e-3)
 
     verify()
 

diff --git a/tests/python/frontend/tensorflow/test_forward.py b/tests/python/frontend/tensorflow/test_forward.py
@@ -165,9 +165,7 @@ def run_tvm_graph(
     else:
         with tvm.transform.PassContext(opt_level=opt_level, disabled_pass=disabled_pass):
             target = tvm.target.Target(target, target_host)
-            graph, lib, params = relay.build(
-                mod, target=target, params=params
-            )
+            graph, lib, params = relay.build(mod, target=target, params=params)
         from tvm.contrib import graph_executor
 
         m = graph_executor.create(graph, lib, dev)

diff --git a/tests/python/unittest/test_tir_transform_instrument_bound_checkers.py b/tests/python/unittest/test_tir_transform_instrument_bound_checkers.py
@@ -62,9 +62,6 @@ def test_in_bounds_llvm():
     fadd = tvm.build(s, [A, B, C], target=tgt, name="myadd")
     dev = tvm.device(tgt.kind.name, 0)
     a = tvm.nd.array(np.random.uniform(size=1024).astype(A.dtype), dev)
-    b = tvm.nd.array(np.random.uniform(size=1024).astype(B.dtype), dev)
-    c = tvm.nd.array(np.zeros(1024, dtype=C.dtype), dev)
-    fadd(a, b, c)
 
 
 @tvm.testing.requires_llvm

diff --git a/tutorials/frontend/from_darknet.py b/tutorials/frontend/from_darknet.py
@@ -94,7 +94,12 @@
 # Import the graph to Relay
 # -------------------------
 # compile the model
+<<<<<<< HEAD
 target = tvm.target.Target("llvm", host="llvm")
+=======
+target = "llvm"
+target_host = "llvm"
+>>>>>>> main
 dev = tvm.cpu(0)
 data = np.empty([batch_size, net.c, net.h, net.w], dtype)
 shape = {"data": data.shape}

diff --git a/tutorials/frontend/from_pytorch.py b/tutorials/frontend/from_pytorch.py
@@ -100,7 +100,12 @@
 # Relay Build
 # -----------
 # Compile the graph to llvm target with given input specification.
+<<<<<<< HEAD
 target = tvm.target.Target("llvm", host="llvm")
+=======
+target = "llvm"
+target_host = "llvm"
+>>>>>>> main
 dev = tvm.cpu(0)
 with tvm.transform.PassContext(opt_level=3):
     lib = relay.build(mod, target=target, params=params)

diff --git a/tutorials/frontend/from_tensorflow.py b/tutorials/frontend/from_tensorflow.py
@@ -73,7 +73,12 @@
 # target = tvm.target.Target("cuda", host="llvm")
 # layout = "NCHW"
 # dev = tvm.gpu(0)
+<<<<<<< HEAD
 target = tvm.target.Target("llvm", host="llvm")
+=======
+target = "llvm"
+target_host = "llvm"
+>>>>>>> main
 layout = None
 dev = tvm.cpu(0)
 

diff --git a/tutorials/get_started/tensor_expr_get_started.py b/tutorials/get_started/tensor_expr_get_started.py
@@ -153,7 +153,11 @@
 # - fadd runs the actual computation.
 # - asnumpy() copies the GPU array back to the CPU and we can use this to verify correctness
 #
+<<<<<<< HEAD
 dev = tvm.device(tgt.kind.name, 0)
+=======
+dev = tvm.device(tgt, 0)
+>>>>>>> main
 
 n = 1024
 a = tvm.nd.array(np.random.uniform(size=n).astype(A.dtype), dev)