[GitHub] [incubator-mxnet] ChaiBapchya commented on a change in pull request #18825: [v1.x][LT] Add forward & backward linalg.gemm test for large size

Thu, 30 Jul 2020 01:37:20 -0700 


ChaiBapchya commented on a change in pull request #18825:
URL: https://github.com/apache/incubator-mxnet/pull/18825#discussion_r462822933



##########
File path: tests/nightly/test_large_array.py
##########
@@ -1211,23 +1211,49 @@ def check_syrk_batch():
         assert_almost_equal(A.grad[1,0,0], nd.array([0.4]), rtol=1e-3, 
atol=1e-5)
 
     def check_gemm2():
-        def run_gemm2(inp1,inp2):
+        def run_gemm2(inp1, inp2):
             inp1.attach_grad()
             inp2.attach_grad()
             with mx.autograd.record():
-                out = mx.nd.linalg.gemm2(inp1,inp2)
+                out = mx.nd.linalg.gemm2(inp1, inp2)
             return inp1.grad, inp2.grad, out
 
-        inp1=mx.nd.ones(shape=(SMALL_Y, LARGE_X))
-        inp1[0][0]=0.1
-        inp2=mx.nd.ones(shape=(LARGE_X, SMALL_Y))
-        inp1_grad, inp2_grad, out= run_gemm2(inp1,inp2)
+        inp1 = mx.nd.ones(shape=(SMALL_Y, LARGE_X))
+        perturbation = 0.2
+        inp1[0][0] = perturbation
+        inp2 = mx.nd.ones(shape=(LARGE_X, SMALL_Y))
+        inp1_grad, inp2_grad, out = run_gemm2(inp1, inp2)
         assert out.asnumpy()[0][0] == LARGE_X
         assert out.shape == (SMALL_Y, SMALL_Y)
         out.backward()
         assert inp1_grad.shape == (SMALL_Y, LARGE_X)
         assert inp2_grad.shape == (LARGE_X, SMALL_Y)
-        assert_almost_equal(inp2_grad.asnumpy()[0][0],49.1)
+        assert_almost_equal(inp1_grad.asnumpy()[0][0], SMALL_Y)
+        assert_almost_equal(inp2_grad.asnumpy()[0][0], SMALL_Y - (1 - 
perturbation))
+
+    def check_gemm():
+        def run_gemm(inp1,inp2, inp3):
+            inp1.attach_grad()
+            inp2.attach_grad()
+            inp3.attach_grad()
+            with mx.autograd.record():
+                out = mx.nd.linalg.gemm(inp1, inp2, inp3, transpose_b=True)
+            return inp1.grad, inp2.grad, inp3.grad, out
+
+        inp1 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X))
+        perturbation = 0.2
+        inp1[0][0][0] = perturbation
+        inp2 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X))

Review comment:
       It's incorrect according to PEP8 style guide Python
   https://www.python.org/dev/peps/pep-0008/
   <img width="895" alt="Screen Shot 2020-07-30 at 1 05 56 AM" 
src="https://user-images.githubusercontent.com/10992635/88897924-e7dbdc00-d200-11ea-987c-e36c6ac58fde.png";>
   

##########
File path: tests/nightly/test_large_array.py
##########
@@ -1211,23 +1211,49 @@ def check_syrk_batch():
         assert_almost_equal(A.grad[1,0,0], nd.array([0.4]), rtol=1e-3, 
atol=1e-5)
 
     def check_gemm2():
-        def run_gemm2(inp1,inp2):
+        def run_gemm2(inp1, inp2):
             inp1.attach_grad()
             inp2.attach_grad()
             with mx.autograd.record():
-                out = mx.nd.linalg.gemm2(inp1,inp2)
+                out = mx.nd.linalg.gemm2(inp1, inp2)
             return inp1.grad, inp2.grad, out
 
-        inp1=mx.nd.ones(shape=(SMALL_Y, LARGE_X))
-        inp1[0][0]=0.1
-        inp2=mx.nd.ones(shape=(LARGE_X, SMALL_Y))
-        inp1_grad, inp2_grad, out= run_gemm2(inp1,inp2)
+        inp1 = mx.nd.ones(shape=(SMALL_Y, LARGE_X))
+        perturbation = 0.2
+        inp1[0][0] = perturbation
+        inp2 = mx.nd.ones(shape=(LARGE_X, SMALL_Y))
+        inp1_grad, inp2_grad, out = run_gemm2(inp1, inp2)
         assert out.asnumpy()[0][0] == LARGE_X
         assert out.shape == (SMALL_Y, SMALL_Y)
         out.backward()
         assert inp1_grad.shape == (SMALL_Y, LARGE_X)
         assert inp2_grad.shape == (LARGE_X, SMALL_Y)
-        assert_almost_equal(inp2_grad.asnumpy()[0][0],49.1)
+        assert_almost_equal(inp1_grad.asnumpy()[0][0], SMALL_Y)
+        assert_almost_equal(inp2_grad.asnumpy()[0][0], SMALL_Y - (1 - 
perturbation))
+
+    def check_gemm():
+        def run_gemm(inp1,inp2, inp3):
+            inp1.attach_grad()
+            inp2.attach_grad()
+            inp3.attach_grad()
+            with mx.autograd.record():
+                out = mx.nd.linalg.gemm(inp1, inp2, inp3, transpose_b=True)
+            return inp1.grad, inp2.grad, inp3.grad, out
+
+        inp1 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X))
+        perturbation = 0.2
+        inp1[0][0][0] = perturbation
+        inp2 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X))
+        inp3 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, SMALL_Y))

Review comment:
       It's incorrect according to PEP8 style guide Python
   https://www.python.org/dev/peps/pep-0008/
   <img width="895" alt="Screen Shot 2020-07-30 at 1 05 56 AM" 
src="https://user-images.githubusercontent.com/10992635/88897924-e7dbdc00-d200-11ea-987c-e36c6ac58fde.png";>
   

##########
File path: tests/nightly/test_large_array.py
##########
@@ -1211,23 +1211,49 @@ def check_syrk_batch():
         assert_almost_equal(A.grad[1,0,0], nd.array([0.4]), rtol=1e-3, 
atol=1e-5)
 
     def check_gemm2():
-        def run_gemm2(inp1,inp2):
+        def run_gemm2(inp1, inp2):
             inp1.attach_grad()
             inp2.attach_grad()
             with mx.autograd.record():
-                out = mx.nd.linalg.gemm2(inp1,inp2)
+                out = mx.nd.linalg.gemm2(inp1, inp2)
             return inp1.grad, inp2.grad, out
 
-        inp1=mx.nd.ones(shape=(SMALL_Y, LARGE_X))
-        inp1[0][0]=0.1
-        inp2=mx.nd.ones(shape=(LARGE_X, SMALL_Y))
-        inp1_grad, inp2_grad, out= run_gemm2(inp1,inp2)
+        inp1 = mx.nd.ones(shape=(SMALL_Y, LARGE_X))
+        perturbation = 0.2
+        inp1[0][0] = perturbation
+        inp2 = mx.nd.ones(shape=(LARGE_X, SMALL_Y))
+        inp1_grad, inp2_grad, out = run_gemm2(inp1, inp2)
         assert out.asnumpy()[0][0] == LARGE_X
         assert out.shape == (SMALL_Y, SMALL_Y)
         out.backward()
         assert inp1_grad.shape == (SMALL_Y, LARGE_X)
         assert inp2_grad.shape == (LARGE_X, SMALL_Y)
-        assert_almost_equal(inp2_grad.asnumpy()[0][0],49.1)
+        assert_almost_equal(inp1_grad.asnumpy()[0][0], SMALL_Y)
+        assert_almost_equal(inp2_grad.asnumpy()[0][0], SMALL_Y - (1 - 
perturbation))
+
+    def check_gemm():
+        def run_gemm(inp1,inp2, inp3):
+            inp1.attach_grad()
+            inp2.attach_grad()
+            inp3.attach_grad()
+            with mx.autograd.record():
+                out = mx.nd.linalg.gemm(inp1, inp2, inp3, transpose_b=True)
+            return inp1.grad, inp2.grad, inp3.grad, out
+
+        inp1 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X))

Review comment:
       It's incorrect according to PEP8 style guide Python
   https://www.python.org/dev/peps/pep-0008/
   <img width="895" alt="Screen Shot 2020-07-30 at 1 05 56 AM" 
src="https://user-images.githubusercontent.com/10992635/88898201-3db08400-d201-11ea-8296-8dbdf9922569.png";>
   




----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

For queries about this service, please contact Infrastructure at:
us...@infra.apache.org

Reply via email to