[GitHub] [incubator-mxnet] ChaiBapchya commented on a change in pull request #18825: [v1.x][LT] Add forward & backward linalg.gemm test for large size
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/ 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/ 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) +
[GitHub] [incubator-mxnet] ChaiBapchya commented on a change in pull request #18825: [v1.x][LT] Add forward & backward linalg.gemm test for large size
ChaiBapchya commented on a change in pull request #18825: URL: https://github.com/apache/incubator-mxnet/pull/18825#discussion_r462741389 ## 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)) Review comment: Addressed ## 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)) +inp1_grad, inp2_grad, inp3_grad, out= run_gemm(inp1, inp2, inp3) Review comment: Addressed ## 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],
