Correction in documentation (#1810)

tests/python/contrib/test_cblas.py

@@ -18,7 +18,7 @@ def test_matmul_add():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.cblas.matmul", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [A, B, D, bias], target)

tests/python/contrib/test_cublas.py

@@ -16,7 +16,7 @@ def test_matmul_add():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.cublas.matmul", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.gpu(0)
         f = tvm.build(s, [A, B, C], target)

tests/python/contrib/test_mps.py

@@ -33,7 +33,7 @@ def test_matmul():
 
     def verify(A, B, D, s, target="metal"):
         if not tvm.get_global_func("tvm.contrib.mps.matmul", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.metal(0)
         f = tvm.build(s, [A, B, D], "metal")
@@ -64,7 +64,7 @@ def test_conv2d():
 
     def verify(A, B, C, target="llvm"):
         if not tvm.get_global_func("tvm.contrib.mps.conv2d", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.metal(0)
         f = tvm.build(s1, [A, B, C], "metal")

tests/python/contrib/test_nnpack.py

@@ -19,7 +19,7 @@ def test_fully_connected_output():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_output", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [A, B, D, bias], target)
@@ -49,7 +49,7 @@ def test_fully_connected_inference():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_inference", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [A, B, D, bias], target)
@@ -128,7 +128,7 @@ def test_convolution_inference():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_inference", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [data, kernel, bias, output], target)
@@ -173,7 +173,7 @@ def test_convolution_output():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_inference", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [data, kernel, bias, output], target)

tests/python/contrib/test_random.py

@@ -13,7 +13,7 @@ def test_randint():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.random.randint", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [A], target)
@@ -37,7 +37,7 @@ def test_uniform():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.random.uniform", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [A], target)
@@ -61,7 +61,7 @@ def test_normal():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.random.normal", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.cpu(0)
         f = tvm.build(s, [A], target)

tests/python/contrib/test_rocblas.py

@@ -16,7 +16,7 @@ def test_matmul_add():
             print("skip because %s is not enabled..." % target)
             return
         if not tvm.get_global_func("tvm.contrib.rocblas.matmul", True):
-            print("skip because extern function is not avalable")
+            print("skip because extern function is not available")
             return
         ctx = tvm.rocm(0)
         f = tvm.build(s, [A, B, C], target)

topi/include/topi/nn.h

@@ -64,7 +64,7 @@ inline tvm::Tensor relu(const tvm::Tensor& t,
 * \param name The name of the operation
 * \param tag The tag to mark the operation
 *
-* \return A Tensor whose op member is the relu operation
+* \return A Tensor whose op member is the leaky relu operation
 */
 inline tvm::Tensor leaky_relu(const tvm::Tensor& t,
                               double alpha = 0.1,
@@ -90,7 +90,7 @@ inline tvm::Tensor leaky_relu(const tvm::Tensor& t,
  * \param name The name of the operation
  * \param tag The tag to mark the operation
  *
- * \return A Tensor whose op member is the relu operation
+ * \return A Tensor whose op member is the parametric relu operation
  */
 inline tvm::Tensor prelu(const tvm::Tensor &x,
                          const tvm::Tensor &slope,