Merge branch 'develop' into propogate-constant

test/onnx/onnx_test.cpp

@@ -15,7 +15,7 @@ TEST_CASE(pytorch_conv_bias_test)
     auto l2       = p.add_parameter("2", {migraphx::shape::float_type, {1}});
     uint64_t axis = 1;
     auto l3       = p.add_instruction(migraphx::op::convolution{}, l0, l1);
-    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
+    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape().lens()}, l2);
     p.add_instruction(migraphx::op::add{}, l3, l4);
 
     auto prog = migraphx::parse_onnx("conv.onnx");
@@ -30,7 +30,7 @@ TEST_CASE(pytorch_conv_relu_maxpool)
     auto l2       = p.add_parameter("2", {migraphx::shape::float_type, {1}});
     uint64_t axis = 1;
     auto l3       = p.add_instruction(migraphx::op::convolution{}, l0, l1);
-    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
+    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape().lens()}, l2);
     auto l5       = p.add_instruction(migraphx::op::add{}, l3, l4);
     auto l6       = p.add_instruction(migraphx::op::relu{}, l5);
     p.add_instruction(migraphx::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
@@ -52,7 +52,7 @@ TEST_CASE(pytorch_conv_bn_relu_maxpool)
     auto p6       = p.add_parameter("6", {migraphx::shape::float_type, {1}});
     uint64_t axis = 1;
     auto l3       = p.add_instruction(migraphx::op::convolution{}, l0, l1);
-    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
+    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape().lens()}, l2);
     auto l5       = p.add_instruction(migraphx::op::add{}, l3, l4);
     auto l6 = p.add_instruction(migraphx::op::batch_norm_inference{1.0e-5f}, l5, p3, p4, p5, p6);
     auto l7 = p.add_instruction(migraphx::op::relu{}, l6);
@@ -70,7 +70,7 @@ TEST_CASE(pytorch_conv_relu_maxpool_x2)
     auto l2       = p.add_parameter("2", {migraphx::shape::float_type, {5}});
     uint64_t axis = 1;
     auto l3       = p.add_instruction(migraphx::op::convolution{}, l0, l1);
-    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
+    auto l4       = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape().lens()}, l2);
     auto l5       = p.add_instruction(migraphx::op::add{}, l3, l4);
     auto l6       = p.add_instruction(migraphx::op::relu{}, l5);
     auto l7 = p.add_instruction(migraphx::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
@@ -78,7 +78,7 @@ TEST_CASE(pytorch_conv_relu_maxpool_x2)
     auto l8  = p.add_parameter("3", {migraphx::shape::float_type, {1, 5, 5, 5}});
     auto l9  = p.add_parameter("4", {migraphx::shape::float_type, {1}});
     auto l10 = p.add_instruction(migraphx::op::convolution{}, l7, l8);
-    auto l11 = p.add_instruction(migraphx::op::broadcast{axis, l10->get_shape()}, l9);
+    auto l11 = p.add_instruction(migraphx::op::broadcast{axis, l10->get_shape().lens()}, l9);
     auto l12 = p.add_instruction(migraphx::op::add{}, l10, l11);
     auto l13 = p.add_instruction(migraphx::op::relu{}, l12);
     p.add_instruction(migraphx::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l13);
@@ -108,9 +108,9 @@ TEST_CASE(imagescaler_test)
     auto scale_val = p.add_literal(0.5f);
     auto bias_vals = p.add_literal(
         migraphx::literal{migraphx::shape{migraphx::shape::float_type, {3}}, {0.01, 0.02, 0.03}});
-    auto scaled_tensor = p.add_instruction(migraphx::op::scalar{s}, scale_val);
+    auto scaled_tensor = p.add_instruction(migraphx::op::scalar{s.lens()}, scale_val);
     auto img_scaled    = p.add_instruction(migraphx::op::mul{}, l0, scaled_tensor);
-    auto bias_bcast    = p.add_instruction(migraphx::op::broadcast{1, s}, bias_vals);
+    auto bias_bcast    = p.add_instruction(migraphx::op::broadcast{1, s.lens()}, bias_vals);
     p.add_instruction(migraphx::op::add{}, img_scaled, bias_bcast);
 
     auto prog = migraphx::parse_onnx("imagescaler_test.onnx");
@@ -338,7 +338,7 @@ TEST_CASE(add_bcast_test)
     migraphx::program p;
     auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
     auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
-    auto l2 = p.add_instruction(migraphx::op::broadcast{1, l0->get_shape()}, l1);
+    auto l2 = p.add_instruction(migraphx::op::broadcast{1, l0->get_shape().lens()}, l1);
     p.add_instruction(migraphx::op::add{}, l0, l2);
 
     auto prog = migraphx::parse_onnx("add_bcast_test.onnx");
@@ -365,7 +365,7 @@ TEST_CASE(sub_bcast_test)
     migraphx::program p;
     auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
     auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
-    auto l2 = p.add_instruction(migraphx::op::broadcast{1, l0->get_shape()}, l1);
+    auto l2 = p.add_instruction(migraphx::op::broadcast{1, l0->get_shape().lens()}, l1);
     p.add_instruction(migraphx::op::sub{}, l0, l2);
 
     auto prog = migraphx::parse_onnx("sub_bcast_test.onnx");

test/op_shape_test.cpp

@@ -229,6 +229,36 @@ TEST_CASE(multibroadcast)
     }
 }
 
+TEST_CASE(broadcast)
+{
+    {
+        std::vector<std::size_t> lens{1, 1};
+        migraphx::shape input{migraphx::shape::float_type, {4, 1, 3}};
+        expect_shape(migraphx::shape{migraphx::shape::float_type, {1, 1}, {0, 0}},
+                     migraphx::op::broadcast{0, lens},
+                     input);
+    }
+    {
+        std::vector<std::size_t> lens{1, 1};
+        migraphx::shape input{migraphx::shape::float_type, {4, 1, 3}};
+        throws_shape(migraphx::op::broadcast{1, lens}, input);
+    }
+
+    {
+        std::vector<std::size_t> lens{3, 2, 4, 3};
+        migraphx::shape input{migraphx::shape::float_type, {4, 3}};
+        expect_shape(migraphx::shape{migraphx::shape::float_type, {3, 2, 4, 3}, {0, 0, 3, 1}},
+                     migraphx::op::broadcast{2, lens},
+                     input);
+    }
+
+    {
+        std::vector<std::size_t> lens{3, 2, 4, 3};
+        migraphx::shape input{migraphx::shape::float_type, {4, 4}};
+        throws_shape(migraphx::op::broadcast{2, lens}, input);
+    }
+}
+
 TEST_CASE(gather)
 {
     {

test/tf/matmul_test.pb

+
+2
+
0Placeholder*
+dtype0
*
+shape
+:
+2
+
1Placeholder*
+dtype0
*
+shape
+:
+F
+matmul1MatMul
0
1*
+
T0
*
+transpose_a(
*
+transpose_b(
"
\ No newline at end of file

test/tf/mul_test.pb

+
+:
+
0Placeholder*
+shape:


*
+dtype0

+:
+
1Placeholder*
+dtype0
*
+shape:



+
+mul1Mul
0
1*
+
T0
"
\ No newline at end of file

test/tf/tf_test.cpp

@@ -63,7 +63,7 @@ TEST_CASE(biasadd_test)
     uint64_t axis = 1;
     auto l0       = p.add_parameter("0", s0);
     auto l1       = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {500}});
-    auto l2       = p.add_instruction(migraphx::op::broadcast{axis, l0->get_shape()}, l1);
+    auto l2       = p.add_instruction(migraphx::op::broadcast{axis, l0->get_shape().lens()}, l1);
     p.add_instruction(migraphx::op::add{}, l0, l2);
     auto prog = migraphx::parse_tf("biasadd_test.pb", true);
 
@@ -129,6 +129,33 @@ TEST_CASE(identity_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(matmul_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {8, 4}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 8}});
+
+    auto trans_l0 = p.add_instruction(migraphx::op::transpose{{1, 0}}, l0);
+    auto trans_l1 = p.add_instruction(migraphx::op::transpose{{1, 0}}, l1);
+
+    p.add_instruction(migraphx::op::dot{}, trans_l0, trans_l1);
+    auto prog = migraphx::parse_tf("matmul_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
+TEST_CASE(mul_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 1, 1, 16}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {1, 1, 1, 16}});
+
+    p.add_instruction(migraphx::op::mul{}, l0, l1);
+    auto prog = migraphx::parse_tf("mul_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(pack_test)
 {
     migraphx::program p;
@@ -237,4 +264,28 @@ TEST_CASE(squeeze_test)
 
     EXPECT(p == prog);
 }
+
+TEST_CASE(stridedslice_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 10, 1, 1}});
+    std::size_t num_axes = 4;
+    migraphx::op::slice op;
+    op.starts = {0, 0, 0, 0};
+    op.ends   = {1, 5, 1, 1};
+    op.axes   = std::vector<int64_t>(num_axes);
+    std::iota(op.axes.begin(), op.axes.end(), 0);
+    // add literals for starts, ends, and strides in tf (NHWC format)
+    p.add_literal(migraphx::shape{migraphx::shape::int32_type, {4}}, std::vector<int>{0, 0, 0, 0});
+    p.add_literal(migraphx::shape{migraphx::shape::int32_type, {4}}, std::vector<int>{1, 1, 1, 5});
+    p.add_literal(migraphx::shape{migraphx::shape::int32_type, {4}}, std::vector<int>{1, 1, 1, 1});
+
+    auto l1          = p.add_instruction(op, l0);
+    auto shrink_axis = 2;
+    p.add_instruction(migraphx::op::squeeze{{shrink_axis}}, l1);
+    auto prog = migraphx::parse_tf("stridedslice_test.pb", true);
+
+    EXPECT(p == prog);
+}
+
 int main(int argc, const char* argv[]) { test::run(argc, argv); }