Shyrma svd (#191)

* - add one additional test for svd

* - provide float argument in eye op to be a type of output array

Signed-off-by: Yurii <yurii@skymind.io>

* - add cuda capability check to mmulHelper

Signed-off-by: Yurii <yurii@skymind.io>

* - make use another method for divice id evaluation

Signed-off-by: Yurii <yurii@skymind.io>

* Eye data type as T argument

Signed-off-by: raver119 <raver119@gmail.com>

libnd4j/include/helpers/cuda_off/MmulHelper.cu

@@ -218,6 +218,9 @@ NDArray* MmulHelper::mmulMxM(const NDArray* A, const NDArray* B, NDArray* C, dou
 
     const bool AB(aType == bType), AC(aType == cType), ABC(AB && AC);
 
+    const int deviceId = AffinityManager::currentDeviceId();
+    const int major = Environment::getInstance()->capabilities()[deviceId].first();
+
     NDArray::prepareSpecialUse({pC}, {pA, pB});
 
     // choose appropriate cuda gemm api depending on data types
@@ -228,20 +231,18 @@ NDArray* MmulHelper::mmulMxM(const NDArray* A, const NDArray* B, NDArray* C, dou
         float alphaF(alpha), betaF(beta);
         status = cublasSgemm(*handle, transAblas, transBblas, M, N, K, &alphaF, (float*)pA->getSpecialBuffer(), lda, (float*)pB->getSpecialBuffer(), ldb, &betaF, (float*)pC->getSpecialBuffer(), ldc);
     }
-#if __CUDA_ARCH__ >= 530
+    else if(ABC && aType == DataType::HALF && major >= 6) {
-    else if(ABC && aType == DataType::HALF) {
         float16 alphaH(alpha), betaH(beta);
         status = cublasHgemm(*handle, transAblas, transBblas, M, N, K, &alphaH.data, (__half*)pA->getSpecialBuffer(), lda, (__half*)pB->getSpecialBuffer(), ldb, &betaH.data, (__half*)pC->getSpecialBuffer(), ldc);
     }
-    else if(AB && aType == DataType::INT8 && cType == DataType::FLOAT32) {
+    else if(AB && aType == DataType::INT8 && cType == DataType::FLOAT32 && major >= 6) {
            float alphaF(alpha), betaF(beta);
            status = cublasSgemmEx(*handle, transAblas, transBblas, M, N, K, &alphaF, pA->getSpecialBuffer(), CUDA_R_8I, lda, pB->getSpecialBuffer(), CUDA_R_8I, ldb, &betaF, pC->getSpecialBuffer(), CUDA_R_32F, ldc);
     }
-    else if(AB && aType == DataType::HALF && cType == DataType::FLOAT32) {
+    else if(AB && aType == DataType::HALF && cType == DataType::FLOAT32  && major >= 6) {
         float alphaF(alpha), betaF(beta);
         status = cublasSgemmEx(*handle, transAblas, transBblas, M, N, K, &alphaF, pA->getSpecialBuffer(), CUDA_R_16F, lda, pB->getSpecialBuffer(), CUDA_R_16F, ldb, &betaF, pC->getSpecialBuffer(), CUDA_R_32F, ldc);
     }
-#endif
     else {
         dim3 threadsPerBlock(N, M);
         dim3 blocksPerGrid(1, 1);

libnd4j/include/ops/declarable/generic/transforms/eye.cpp

@@ -27,7 +27,7 @@ namespace nd4j {
 namespace ops {
 
 
-    CUSTOM_OP_IMPL(eye, -2, 1, false, 0, -2) {
+    CUSTOM_OP_IMPL(eye, -2, 1, false, -2, -2) {
 
         helpers::eye(block.launchContext(), *OUTPUT_VARIABLE(0));
 
@@ -44,8 +44,7 @@ namespace ops {
 
         std::vector<int> params;
 
-        // FIX ME: original has a dtype param - so should be used here instead. e.g. (DataType) INT_ARG(0);
+        nd4j::DataType dtype = block.getTArguments()->empty() ? nd4j::DataType::FLOAT32 : nd4j::DataTypeUtils::fromInt(T_ARG(0));
-        nd4j::DataType dtype = nd4j::DataType::FLOAT32;
 
         if(block.width() == 0) {
             params = *block.getIArguments();
@@ -54,20 +53,20 @@ namespace ops {
             for (int i = 0; i < block.width(); i++) {
                 auto input = INPUT_VARIABLE(i);
                 REQUIRE_TRUE(input->rankOf() == 1, 0, "Inputs to eye should be 1D");
-                for (int e = 0; e < input->lengthOf(); e++) {
+
+                for (int e = 0; e < input->lengthOf(); e++)
                     params.emplace_back(input->e<int>(e));
             }
         }
-        }
 
 
-        REQUIRE_TRUE(params.size() > 0, 0, "Size not provided for eye op.");
+        REQUIRE_TRUE(params.size() > 0, 0, "Size is not provided for eye op.");
 
         const bool ordered = (params[0] == -99 || params[0] == -102); // -99 :'c', -102 : 'f'
         if (!ordered)
             params.insert(params.begin(), -99);
 
-        REQUIRE_TRUE(params.size() > 1, 0, "Size not provided for eye op.");
+        REQUIRE_TRUE(params.size() > 1, 0, "Size is not provided for eye op.");
 
         Nd4jLong* outShapeInfo(nullptr);
 

libnd4j/include/ops/declarable/headers/transforms.h

@@ -115,6 +115,9 @@ namespace nd4j {
          * Input array:
          * provide some array - in any case operation simply neglects it
          *
+         * Input float argument (if passed):
+         * TArgs[0] - type of elements of output array, default value is 5 (float)
+         *
          * Input integer arguments:
          * IArgs[0]       - order of output identity matrix, 99 -> 'c'-order, 102 -> 'f'-order
          * IArgs[1]       - the number of rows in output inner-most 2D identity matrix
@@ -122,7 +125,7 @@ namespace nd4j {
          * IArgs[3,4,...] - optional, shape of batch, output matrix will have leading batch dimensions of this shape
          */
         #if NOT_EXCLUDED(OP_eye)
-        DECLARE_CUSTOM_OP(eye, -2, 1, false, 0, 2);
+        DECLARE_CUSTOM_OP(eye, -2, 1, false, -2, 2);
         #endif
 
         #if NOT_EXCLUDED(OP_gather_nd)

libnd4j/tests_cpu/layers_tests/CudaBasicsTests2.cu

@@ -272,6 +272,7 @@ TEST_F(CudaBasicsTests2, mmulMxM_12) {
 	NDArray exp('f', {M,N}, {-16., -22., -23., -25., 30., -12., -38., -70., 20., 16., 18., 18., 22., -8., -28., -52.}, nd4j::DataType::FLOAT32);
 
 	nd4j::MmulHelper::mmul(&a, &b, &c, 1., 0.);
+	// c.printBuffer();
 
 	ASSERT_TRUE(c.equalsTo(&exp));
 }

libnd4j/tests_cpu/layers_tests/DeclarableOpsTests3.cpp

@@ -2757,10 +2757,18 @@ TEST_F(DeclarableOpsTests3, svd_test10) {
 ///////////////////////////////////////////////////////////////////
 TEST_F(DeclarableOpsTests3, svd_test11) {
 
-    auto x = NDArrayFactory::create<double>('c', {3,3}, {1.,2.,3.,4.,5.,6.,7.,8.,9.});
+    NDArray x('c', {2,2,3,3}, {0.7788, 0.8012, 0.7244, 0.2309, 0.7271, 0.1804, 0.5056, 0.8925, 0.5461, 0.9234, 0.0856, 0.7938, 0.6591, 0.5555,
-    auto expS = NDArrayFactory::create<double>('c', {3});
+                                0.1596, 0.3087, 0.1548, 0.4695, 0.7788, 0.8012, 0.7244, 0.2309, 0.7271, 0.1804, 0.5056, 0.8925, -0.5461, 0.9234,
-    auto expU = NDArrayFactory::create<double>('c', {3,3});
+                                0.0856, -0.7938, 0.6591, 0.5555, 0.1500, 0.3087, 0.1548, 0.4695});
-    auto expV = NDArrayFactory::create<double>('c', {3,3});
+    NDArray expS('c', {2,2,3}, {1.89671, 0.37095, 0.05525,1.51296, 0.52741, 0.17622, 1.69095, 0.90438, 0.24688,1.33551, 0.87475, 0.21571});
+    NDArray expU('c', {2,2,3,3}, {6.9205e-01,  6.0147e-01, -3.9914e-01, 3.8423e-01, -7.7503e-01, -5.0170e-01, 6.1110e-01, -1.9384e-01,  7.6746e-01,
+                                7.8967e-01,  4.5442e-01, -4.1222e-01, 4.9381e-01, -8.6948e-01, -1.2540e-02, 3.6412e-01,  1.9366e-01,  9.1100e-01,
+                                7.1764e-01,  5.9844e-01,  3.5617e-01, 4.4477e-01, -3.1000e-04, -8.9564e-01, 5.3588e-01, -8.0116e-01,  2.6639e-01,
+                                8.7050e-01, -4.2088e-01, -2.5513e-01, 4.8622e-01,  6.5499e-01,  5.7843e-01, 7.6340e-02,  6.2757e-01, -7.7481e-01});
+    NDArray expV('c', {2,2,3,3}, {0.49383,  0.51614, -0.69981, 0.72718, -0.68641,  0.00688, 0.4768 ,  0.51228,  0.7143 , 0.77137, -0.17763,
+                                  -0.6111 , 0.26324, -0.7852 ,  0.56051, 0.57939,  0.59322,  0.55892, 0.55149,  0.06737,  0.83146, 0.81413,
+                                  -0.26072, -0.51887, 0.18182,  0.96306, -0.19863, 0.85948,  0.2707 , -0.4336 , 0.26688,  0.48582,  0.83232,
+                                  -0.43596,  0.83108, -0.34531});
 
     nd4j::ops::svd op;
     auto results = op.execute({&x}, {}, {0, 1, 16});
@@ -2775,6 +2783,10 @@ TEST_F(DeclarableOpsTests3, svd_test11) {
     ASSERT_TRUE(expU.isSameShape(u));
     ASSERT_TRUE(expV.isSameShape(v));
 
+    ASSERT_TRUE(expS.equalsTo(s));
+    ASSERT_TRUE(expU.equalsTo(u));
+    ASSERT_TRUE(expV.equalsTo(v));
+
     delete results;
 }
 

libnd4j/tests_cpu/layers_tests/DeclarableOpsTests5.cpp

@@ -639,10 +639,10 @@ TEST_F(DeclarableOpsTests5, eye_test2) {
 //////////////////////////////////////////////////////////////////////
 TEST_F(DeclarableOpsTests5, eye_test3) {
 
-    auto expected = NDArrayFactory::create<float>('c', {2, 3, 4}, {1,  0,  0,  0, 0,  1,  0,  0, 0,  0,  1,  0, 1,  0,  0,  0, 0,  1,  0,  0, 0,  0,  1,  0});
+    auto expected = NDArrayFactory::create<int>('c', {2, 3, 4}, {1,  0,  0,  0, 0,  1,  0,  0, 0,  0,  1,  0, 1,  0,  0,  0, 0,  1,  0,  0, 0,  0,  1,  0});
 
     nd4j::ops::eye op;
-    auto results = op.execute({}, {}, {-99, 3, 4, 2});
+    auto results = op.execute({}, {9 /*int*/}, {-99, 3, 4, 2});
     auto output = results->at(0);
      // output->printIndexedBuffer("Output eye");
 
@@ -656,10 +656,10 @@ TEST_F(DeclarableOpsTests5, eye_test3) {
 //////////////////////////////////////////////////////////////////////
 TEST_F(DeclarableOpsTests5, eye_test4) {
 
-    auto expected = NDArrayFactory::create<float>('c', {2, 2, 3, 4}, {1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0., 1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0., 1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0., 1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0.});
+    auto expected = NDArrayFactory::create<double>('c', {2, 2, 3, 4}, {1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0., 1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0., 1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0., 1.,  0.,  0.,  0., 0.,  1.,  0.,  0., 0.,  0.,  1.,  0.});
 
     nd4j::ops::eye op;
-    auto results = op.execute({}, {}, {-99, 3, 4, 2, 2});
+    auto results = op.execute({}, {6/*double*/}, {-99, 3, 4, 2, 2});
     auto output = results->at(0);
 
     ASSERT_EQ(Status::OK(), results->status());

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/shape/Eye.java

@@ -98,6 +98,9 @@ public class Eye extends DynamicCustomOp {
     }
 
     protected void addArgs() {
+        iArguments.clear();
+        tArguments.clear();
+
         addIArgument(numRows);
         addIArgument(numCols);
         if(batchDimension != null) {
@@ -105,6 +108,8 @@ public class Eye extends DynamicCustomOp {
                 addIArgument(dim);
             }
         }
+
+        addTArgument((double) dataType.toInt());
     }
 
     @Override