//-------------------------------------------------------------------------------------------------- // Test expected errors generated by verifier checks. //-------------------------------------------------------------------------------------------------- // RUN: mlir-opt %s -split-input-file -verify-diagnostics // ----- func.func @test_transpose_io_rank_mismatch(%arg0: tensor<13x21x3xf32>, %arg1: tensor<3xi32>) -> tensor<3x13x21x1xf32> { // expected-error@+1 {{'tosa.transpose' op expected input tensor rank to equal result tensor rank}} %0 = tosa.transpose %arg0 {perms = array}: (tensor<13x21x3xf32>) -> tensor<3x13x21x1xf32> return %0 : tensor<3x13x21x1xf32> } // ----- func.func @test_transpose_rank0_perms() { %14 = tensor.empty() : tensor<5x27xi64> // expected-error@+1 {{'tosa.transpose' op expected perms attribute to have size 2 (input rank) but got size 0}} %72 = tosa.transpose %14 {perms = array }: (tensor<5x27xi64>) -> tensor return } // ----- func.func @test_transpose_invalid_perms_size(%arg0: tensor<13x21x3xf32>) -> tensor<3x13x21xf32> { // expected-error@+1 {{'tosa.transpose' op expected perms attribute to have size 3 (input rank) but got size 7}} %0 = tosa.transpose %arg0 {perms = array }: (tensor<13x21x3xf32>) -> tensor<3x13x21xf32> return %0 : tensor<3x13x21xf32> } // ----- func.func @test_transpose_invalid_permutation_tensor(%arg0: tensor<13x21x3xf32>) -> tensor { // expected-error@+1 {{'tosa.transpose' op expected valid permutation indices}} %0 = tosa.transpose %arg0 {perms = array }: (tensor<13x21x3xf32>) -> tensor return %0 : tensor } // ----- func.func @test_transpose_invalid_permutation_negative(%arg0: tensor<3x2xi32>) -> tensor<*xi32> { // expected-error@+1 {{'tosa.transpose' op expected valid permutation indices}} %1 = tosa.transpose %arg0 {perms = array }: (tensor<3x2xi32>) -> tensor<*xi32> return %1 : tensor<*xi32> } // ----- func.func @test_transpose_invalid_permutation_tensor_above_range(%arg0: tensor<3x2xi32>) -> tensor<*xi32> { // expected-error@+1 {{'tosa.transpose' op expected valid permutation indices}} %1 = tosa.transpose %arg0 {perms = array }: (tensor<3x2xi32>) -> tensor<*xi32> return %1 : tensor<*xi32> } // ----- func.func @test_transpose_invalid_num_elements(%arg0: tensor<3x2xi32>) -> tensor<3x4xi32> { // expected-error@+1 {{'tosa.transpose' op expected input1 and output to have same numbers of elements, got 6 and 12}} %1 = tosa.transpose %arg0 {perms = array }: (tensor<3x2xi32>) -> tensor<3x4xi32> return %1 : tensor<3x4xi32> } // ----- func.func @test_transpose_invalid_permutation_types(%arg0: tensor<3x2xi32>) -> tensor<3x2xi32> { // expected-error@+1 {{'tosa.transpose' op expected output tensor dim 0 to match input dim 1 with value of 2}} %1 = tosa.transpose %arg0 {perms = array }: (tensor<3x2xi32>) -> tensor<3x2xi32> return %1 : tensor<3x2xi32> } // ----- func.func @test_transpose_invalid_permutation_types_dynamic_dim_ok(%arg0: tensor<2x?xi32>) -> tensor<3x4xi32> { // expected-error@+1 {{'tosa.transpose' op expected output tensor dim 1 to match input dim 0 with value of 2}} %1 = tosa.transpose %arg0 {perms = array }: (tensor<2x?xi32>) -> tensor<3x4xi32> return %1 : tensor<3x4xi32> } // ----- func.func @test_transpose_element_type_mismatch(%arg0: tensor<2x3xi32>) -> tensor<3x2xf32> { // expected-error@+1 {{'tosa.transpose' op failed to verify that all of {input1, output} have same element type}} %1 = tosa.transpose %arg0 {perms = array} : (tensor<2x3xi32>) -> tensor<3x2xf32> return %1 : tensor<3x2xf32> } // ----- // CHECK-LABEL: @test_invalid_constant_permutation func.func @test_invalid_constant_permutation() { %0 = tensor.empty() : tensor<3x4x5xi32> // expected-error@+1 {{'tosa.transpose' op expected valid permutation indices}} %2 = tosa.transpose %0 {perms = array}: (tensor<3x4x5xi32>) -> tensor<3x4x5xi32> return } // ----- // CHECK-LABEL: test_rank_size_constant_permutation func.func @test_rank_size_constant_permutation() { %0 = arith.constant 6 : index %2 = tensor.empty(%0) : tensor // expected-error@+1 {{'tosa.transpose' op expected valid permutation indices}} %3 = tosa.transpose %2 {perms = array}: (tensor) -> tensor return } // ----- // CHECK-LABEL: test_large_constant_permutation func.func @test_large_constant_permutation() { %0 = arith.constant 6 : index %2 = tensor.empty(%0) : tensor // expected-error@+1 {{'tosa.transpose' op expected valid permutation indices}} %3 = tosa.transpose %2 {perms = array}: (tensor) -> tensor return } // ----- func.func @test_scalar_output_transpose(%arg0: tensor<*xf32>) -> tensor { // expected-error@+1 {{'tosa.transpose' op result #0 must be tosa-conformant tensor of at least rank 1, but got 'tensor'}} %1 = tosa.transpose %arg0 {perms = array} : (tensor<*xf32>) -> tensor return %1 : tensor } // ----- func.func @test_reverse_element_type_mismatch(%arg0: tensor<2x3xi32>) -> tensor<2x3xf32> { // expected-error@+1 {{'tosa.reverse' op requires the same element type for all operands and results}} %0 = tosa.reverse %arg0 {axis = 1 : i32} : (tensor<2x3xi32>) -> tensor<2x3xf32> return %0 : tensor<2x3xf32> } // ----- func.func @test_reverse_shape_mismatch(%arg0: tensor<2x3xi32>) -> tensor<2x4xi32> { // expected-error@+1 {{'tosa.reverse' op requires the same shape for all operands and results}} %0 = tosa.reverse %arg0 {axis = 1 : i32} : (tensor<2x3xi32>) -> tensor<2x4xi32> return %0 : tensor<2x4xi32> } // ----- func.func @test_reverse_rank_mismatch(%arg0: tensor<2x3xi32>) -> tensor<1x2x3xi32> { // expected-error@+1 {{'tosa.reverse' op result type has different rank than operands}} %0 = tosa.reverse %arg0 {axis = 1 : i32} : (tensor<2x3xi32>) -> tensor<1x2x3xi32> return %0 : tensor<1x2x3xi32> } // ----- func.func @test_slice_invalid_output_rank() { %0 = tensor.empty() : tensor<4x31x31xf32> %start = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2> %size = tosa.const_shape {values = dense<[1, 1, 1]> : tensor<3xindex>} : () -> !tosa.shape<3> // expected-error@+1 {{'tosa.slice' op expect input1 and output to have the same ranks, got 3 and 4}} %3 = tosa.slice %0, %start, %size : (tensor<4x31x31xf32>, !tosa.shape<2>, !tosa.shape<3>) -> tensor return } // ----- func.func @test_slice_invalid_start() { %0 = tensor.empty() : tensor<4x31x31xf32> %start = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2> %size = tosa.const_shape {values = dense<[1, 1, 1]> : tensor<3xindex>} : () -> !tosa.shape<3> // expected-error@+1 {{'tosa.slice' op length of start is not equal to rank of input shape}} %3 = tosa.slice %0, %start, %size : (tensor<4x31x31xf32>, !tosa.shape<2>, !tosa.shape<3>) -> tensor<*xf32> return } // ----- func.func @test_slice_invalid_size() { %0 = tensor.empty() : tensor<4x31x31xf32> %start = tosa.const_shape {values = dense<[1, 1, 1]> : tensor<3xindex>} : () -> !tosa.shape<3> %size = tosa.const_shape {values = dense<[1]> : tensor<1xindex>} : () -> !tosa.shape<1> // expected-error@+1 {{'tosa.slice' op length of size is not equal to rank of input shape}} %3 = tosa.slice %0, %start, %size : (tensor<4x31x31xf32>, !tosa.shape<3>, !tosa.shape<1>) -> tensor<*xf32> return } // ----- func.func @test_scalar_slice(%arg0: tensor) -> tensor { %0 = tosa.const_shape {values = dense<[]> : tensor<0xindex>} : () -> !tosa.shape<0> %1 = tosa.const_shape {values = dense<[]> : tensor<0xindex>} : () -> !tosa.shape<0> // expected-error@+1 {{'tosa.slice' op operand #0 must be tosa-conformant tensor of at least rank 1, but got 'tensor'}} %2 = tosa.slice %arg0, %0, %1 : (tensor, !tosa.shape<0>, !tosa.shape<0>) -> tensor return %2 : tensor } // ----- func.func @test_slice_invalid_start_values(%arg0: tensor<4x31x31xf32>) { %start = tosa.const_shape {values = dense<[-2, 0, 0]> : tensor<3xindex>} : () -> !tosa.shape<3> %size = tosa.const_shape {values = dense<[1, 1, 1]> : tensor<3xindex>} : () -> !tosa.shape<3> // expected-error@+1 {{'tosa.slice' op start values must be non-negative, got [-2, 0, 0]}} %1 = tosa.slice %arg0, %start, %size : (tensor<4x31x31xf32>, !tosa.shape<3>, !tosa.shape<3>) -> tensor<1x1x1xf32> return } // ----- func.func @test_slice_invalid_size_values(%arg0: tensor<4x31x31xf32>) { %start = tosa.const_shape {values = dense<[0, 0, 0]> : tensor<3xindex>} : () -> !tosa.shape<3> %size = tosa.const_shape {values = dense<[1, 0, 1]> : tensor<3xindex>} : () -> !tosa.shape<3> // expected-error@+1 {{'tosa.slice' op size values must be > 0, got [1, 0, 1]}} %1 = tosa.slice %arg0, %start, %size : (tensor<4x31x31xf32>, !tosa.shape<3>, !tosa.shape<3>) -> tensor return } // ----- func.func @test_slice_output_shape_mismatch(%arg0: tensor<4x5x6xf32>) { %start = tosa.const_shape {values = dense<[0, 0, 0]> : tensor<3xindex>} : () -> !tosa.shape<3> %size = tosa.const_shape {values = dense<[1, 2, 3]> : tensor<3xindex>} : () -> !tosa.shape<3> // expected-error@+1 {{'tosa.slice' op expected output shape to match size values, got 'tensor<1x2x4xf32>' vs [1, 2, 3]}} %1 = tosa.slice %arg0, %start, %size : (tensor<4x5x6xf32>, !tosa.shape<3>, !tosa.shape<3>) -> tensor<1x2x4xf32> return } // ----- func.func @test_slice_invalid_start_plus_size(%arg0: tensor) { %start = tosa.const_shape {values = dense<[-1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2> %size = tosa.const_shape {values = dense<[3, 2]> : tensor<2xindex>} : () -> !tosa.shape<2> // expected-error@+1 {{'tosa.slice' op start + size must be less than or equal to input dimension size, got start=1, size=2 vs input dim size=2 at dimension 1}} %1 = tosa.slice %arg0, %start, %size : (tensor, !tosa.shape<2>, !tosa.shape<2>) -> tensor return } // ----- func.func @test_slice_output_shape_mismatch_dynamic(%arg0: tensor) { %start = tosa.const_shape {values = dense<[0, 0, 0]> : tensor<3xindex>} : () -> !tosa.shape<3> %size = tosa.const_shape {values = dense<[1, 2, 3]> : tensor<3xindex>} : () -> !tosa.shape<3> // expected-error@+1 {{'tosa.slice' op expected output shape to match size values, got 'tensor' vs [1, 2, 3]}} %1 = tosa.slice %arg0, %start, %size : (tensor, !tosa.shape<3>, !tosa.shape<3>) -> tensor return } // ----- func.func @test_depthwise_conv2d_invalid_padding(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<8xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x4x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op expect all padding values to be >= 0, got 0, 0, -1, 0}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<8xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x4x8xf32> return %0 : tensor<1x4x4x8xf32> } // ----- func.func @test_depthwise_conv2d_invalid_stride(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<8xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x4x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op expect all stride values to be >= 1, got 0, 1}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<8xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x4x8xf32> return %0 : tensor<1x4x4x8xf32> } // ----- func.func @test_depthwise_conv2d_invalid_dilation(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<8xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x4x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op expect all dilation values to be >= 1, got 1, 0}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<8xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x4x8xf32> return %0 : tensor<1x4x4x8xf32> } // ----- func.func @test_depthwise_conv2d_wholly_divisible_height(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<8xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x4x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op expected input_height - 1 + pad_top + pad_bottom - (kernel_height - 1) * dilation_y to be wholly divisible by stride_y, got (4 - 1 + 0 + 0 - (1 - 1) * 1) / 2}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<8xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x4x8xf32> return %0 : tensor<1x4x4x8xf32> } // ----- func.func @test_depthwise_conv2d_wholly_divisible_width(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<8xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x4x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op expected input_width - 1 + pad_left + pad_right - (kernel_width - 1) * dilation_x to be wholly divisible by stride_x, got (4 - 1 + 0 + 0 - (1 - 1) * 1) / 2}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<8xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x4x8xf32> return %0 : tensor<1x4x4x8xf32> } // ----- func.func @test_depthwise_conv2d_unexpected_output_height(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<8xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x6x4x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op calculated output height did not match expected: calculated=4, expected=6}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<8xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x6x4x8xf32> return %0 : tensor<1x6x4x8xf32> } // ----- func.func @test_depthwise_conv2d_unexpected_output_width(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<8xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x6x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op calculated output width did not match expected: calculated=4, expected=6}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<8xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x6x8xf32> return %0 : tensor<1x4x6x8xf32> } // ----- func.func @test_depthwise_conv2d_invalid_bias_size(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x8x4xf32>, %arg2: tensor<7xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x4x8xf32> { // expected-error@+1 {{'tosa.depthwise_conv2d' op bias channels expected to be equal to output channels (8) or 1, got 7}} %0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array, local_bound = true} : (tensor<1x4x4x4xf32>, tensor<1x1x8x4xf32>, tensor<7xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x4x8xf32> return %0 : tensor<1x4x4x8xf32> } // ----- func.func @test_conv3d_invalid_padding(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op expect all padding values to be >= 0, got 0, -1, 0, -1, 0, 0}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32> return %0 : tensor<1x4x8x21x34xf32> } // ----- func.func @test_conv3d_invalid_stride(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op expect all stride values to be >= 1, got 0, 1, 1}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32> return %0 : tensor<1x4x8x21x34xf32> } // ----- func.func @test_conv3d_invalid_dilation(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op expect all dilation values to be >= 1, got 1, 0, 1}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32> return %0 : tensor<1x4x8x21x34xf32> } // ----- func.func @test_conv3d_wholly_divisible_input_depth(%arg0: tensor<1x4x16x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op expected input_depth - 1 + pad_front + pad_back - (kernel_depth - 1) * dilation_d to be wholly divisible by stride_d, got (4 - 1 + 0 + 0 - (1 - 1) * 1) / 2}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x16x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32> return %0 : tensor<1x4x8x21x34xf32> } // ----- func.func @test_conv3d_wholly_divisible_input_height(%arg0: tensor<1x4x10x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op expected input_height - 1 + pad_top + pad_bottom - (kernel_height - 1) * dilation_y to be wholly divisible by stride_y, got (10 - 1 + 0 + 0 - (1 - 1) * 1) / 4}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x10x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32> return %0 : tensor<1x4x8x21x34xf32> } // ----- func.func @test_conv3d_wholly_divisible_input_width(%arg0: tensor<1x4x8x21x19xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op expected input_width - 1 + pad_left + pad_right - (kernel_width - 1) * dilation_x to be wholly divisible by stride_x, got (21 - 1 + 0 + 0 - (1 - 1) * 1) / 8}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x8x21x19xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32> return %0 : tensor<1x4x8x21x34xf32> } // ----- func.func @test_conv3d_wholly_divisible_output_depth(%arg0: tensor<1x4x10x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x3x10x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op calculated output depth did not match expected: calculated=4, expected=3}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x10x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x3x10x21x34xf32> return %0 : tensor<1x3x10x21x34xf32> } // ----- func.func @test_conv3d_wholly_divisible_output_height(%arg0: tensor<1x4x16x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> { // expected-error@+1 {{'tosa.conv3d' op calculated output height did not match expected: calculated=16, expected=8}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x16x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32> return %0 : tensor<1x4x8x21x34xf32> } // ----- func.func @test_conv3d_wholly_divisible_output_width(%arg0: tensor<1x4x8x21x19xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x19x34xf32> { // expected-error@+1 {{'tosa.conv3d' op calculated output width did not match expected: calculated=21, expected=19}} %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array, pad = array, stride = array} : (tensor<1x4x8x21x19xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x19x34xf32> return %0 : tensor<1x4x8x19x34xf32> } // ----- func.func @test_concat_element_type_mismatch(%arg0 : tensor<1x2xf32>, %arg1 : tensor<2x2xf32>) -> tensor { // expected-error@+1 {{'tosa.concat' op expect input and output to have same element type, got 'f32' and 'i8'}} %0 = tosa.concat %arg0, %arg1 {axis = 0 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor return %0 : tensor } // ----- func.func @test_concat_zero_inputs() { // expected-error@+1 {{'tosa.concat' op expect at least one input}} %0 = tosa.concat {axis = 0 : i32} : () -> tensor<*xf32> } // ----- func.func @test_concat_axis_negative(%arg0: tensor<1x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> { // expected-error@+1 {{'tosa.concat' op expect axis to be within range 0 < axis < rank(input1[firstRankedTensorIdx]), got -1}} %0 = tosa.concat %arg0, %arg1 {axis = -1 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32> return %0 : tensor<2x2xf32> } // ----- func.func @test_concat_axis_out_of_range(%arg0: tensor<1x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> { // expected-error@+1 {{'tosa.concat' op expect axis to be within range 0 < axis < rank(input1[firstRankedTensorIdx]), got 3}} %0 = tosa.concat %arg0, %arg1 {axis = 3 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32> return %0 : tensor<2x2xf32> } // ----- func.func @test_concat_axis_sum_error(%arg0: tensor<1x2xf32>, %arg1: tensor<2x?xf32>) -> tensor<2x?xf32> { // expected-error@+1 {{'tosa.concat' op requires sum of axis dimensions of input1 equal to output axis dimension, got 3 and 2}} %0 = tosa.concat %arg0, %arg1 {axis = 0 : i32} : (tensor<1x2xf32>, tensor<2x?xf32>) -> tensor<2x?xf32> return %0 : tensor<2x?xf32> } // ----- func.func @test_error_scalar_input_with_per_channel(%arg0: tensor) -> tensor { %multiplier = "tosa.const"() {values = dense<4> : tensor<1xi32> } : () -> tensor<1xi32> %shift = "tosa.const"() {values = dense<2> : tensor<1xi8> } : () -> tensor<1xi8> %input_zp = "tosa.const"() {values = dense<0> : tensor<1xi8>} : () -> tensor<1xi8> %output_zp = "tosa.const"() {values = dense<0> : tensor<1xi16>} : () -> tensor<1xi16> // expected-error@+1 {{'tosa.rescale' op requires input to be at least rank 1 when per_channel is true, but got rank 0}} %0 = tosa.rescale %arg0, %multiplier, %shift, %input_zp, %output_zp {scale32 = true, rounding_mode = SINGLE_ROUND, per_channel = true, input_unsigned = false, output_unsigned = false} : (tensor, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi16>) -> tensor return %0 : tensor } // ----- func.func @test_rescale_invalid_static_output_shape(%arg0: tensor<13x21x3xi8>) -> tensor<13x21x4xi8> { %multiplier = "tosa.const"() <{values = dense<42> : tensor<1xi16>}> : () -> tensor<1xi16> %shift = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8> %input_zp = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8> %output_zp = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8> // expected-error@+1 {{'tosa.rescale' op expected output shape 13, 21, 4 to be compatible with inferred shape 13, 21, 3}} %0 = tosa.rescale %arg0, %multiplier, %shift, %input_zp, %output_zp {scale32 = false, rounding_mode = SINGLE_ROUND, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<13x21x3xi8>, tensor<1xi16>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<13x21x4xi8> return %0 : tensor<13x21x4xi8> } // ----- func.func @test_mul_invalid_static_output_shape(%arg0: tensor, %arg1: tensor) -> tensor { %shift = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8> // expected-error@+1 {{'tosa.mul' op expected output shape ?, 21, 2 to be compatible with inferred shape ?, 21, 3}} %0 = tosa.mul %arg0, %arg1, %shift : (tensor, tensor, tensor<1xi8>) -> tensor return %0 : tensor } // ----- // CHECK-LABEL: @test_gather_invalid_indices_N func.func @test_gather_invalid_indices_N(%arg0: tensor<13x21x3xf32>, %arg1: tensor<12x26xi32>) -> tensor<13x26x3xf32> { // expected-error@+1 {{'tosa.gather' op requires indices dimension 0 to have size 13, got 12}} %0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xf32>, tensor<12x26xi32>) -> tensor<13x26x3xf32> return %0 : tensor<13x26x3xf32> } // ----- // CHECK-LABEL: test_gather_invalid_out_N func.func @test_gather_invalid_out_N(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>) -> tensor<12x26x3xf32> { // expected-error@+1 {{'tosa.gather' op requires output dimension 0 to have size 13, got 12}} %0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xf32>, tensor<13x26xi32>) -> tensor<12x26x3xf32> return %0 : tensor<12x26x3xf32> } // ----- // CHECK-LABEL: test_gather_invalid_out_W func.func @test_gather_invalid_out_W(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>) -> tensor<13x28x3xf32> { // expected-error@+1 {{'tosa.gather' op requires output dimension 1 to have size 26, got 28}} %0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xf32>, tensor<13x26xi32>) -> tensor<13x28x3xf32> return %0 : tensor<13x28x3xf32> } // ----- // CHECK-LABEL: test_gather_invalid_out_C func.func @test_gather_invalid_out_C(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>) -> tensor<13x26x8xf32> { // expected-error@+1 {{'tosa.gather' op requires output dimension 2 to have size 3, got 8}} %0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xf32>, tensor<13x26xi32>) -> tensor<13x26x8xf32> return %0 : tensor<13x26x8xf32> } // ----- // CHECK-LABEL: test_row_gather_block_scaled_output_count_mismatch func.func @test_row_gather_block_scaled_output_count_mismatch(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>) -> (tensor<13x52x3xf32>, tensor<13x52x3xf32>) { %row_count = "tosa.const"() {values = dense<2> : tensor<1xi32>} : () -> tensor<1xi32> // expected-error@+1 {{'tosa.row_gather_block_scaled' op expects output tensor list length to match values tensor list length, got 2 results for 1 input tensors}} %0:2 = tosa.row_gather_block_scaled %arg0, %arg1, %row_count {block_size = #tosa.block_size} : (tensor<13x21x3xf32>, tensor<13x26xi32>, tensor<1xi32>) -> (tensor<13x52x3xf32>, tensor<13x52x3xf32>) return %0#0, %0#1 : tensor<13x52x3xf32>, tensor<13x52x3xf32> } // ----- // CHECK-LABEL: test_row_gather_block_scaled_block_size_one_required func.func @test_row_gather_block_scaled_block_size_one_required(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>) -> tensor<13x52x3xf32> { %row_count = "tosa.const"() {values = dense<2> : tensor<1xi32>} : () -> tensor<1xi32> // expected-error@+1 {{'tosa.row_gather_block_scaled' op requires block_size to be BLOCK_SIZE_1 when values tensor list length is 1}} %0 = tosa.row_gather_block_scaled %arg0, %arg1, %row_count {block_size = #tosa.block_size} : (tensor<13x21x3xf32>, tensor<13x26xi32>, tensor<1xi32>) -> (tensor<13x52x3xf32>) return %0 : tensor<13x52x3xf32> } // ----- // CHECK-LABEL: test_row_gather_block_scaled_output_rows_mismatch func.func @test_row_gather_block_scaled_output_rows_mismatch(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>) -> tensor<13x53x3xf32> { %row_count = "tosa.const"() {values = dense<2> : tensor<1xi32>} : () -> tensor<1xi32> // expected-error@+1 {{'tosa.row_gather_block_scaled' op requires output[0] dimension 1 to have size 52, got 53}} %0 = tosa.row_gather_block_scaled %arg0, %arg1, %row_count {block_size = #tosa.block_size} : (tensor<13x21x3xf32>, tensor<13x26xi32>, tensor<1xi32>) -> (tensor<13x53x3xf32>) return %0 : tensor<13x53x3xf32> } // ----- // CHECK-LABEL: test_row_gather_block_scaled_scale_channel_mismatch func.func @test_row_gather_block_scaled_scale_channel_mismatch(%arg0: tensor<13x21x32xf4E2M1FN>, %arg1: tensor<13x21x2xf8E8M0FNU>, %arg2: tensor<13x26xi32>) -> (tensor<13x52x32xf4E2M1FN>, tensor<13x52x2xf8E8M0FNU>) { %row_count = "tosa.const"() {values = dense<2> : tensor<1xi32>} : () -> tensor<1xi32> // expected-error@+1 {{'tosa.row_gather_block_scaled' op expects channels of scale tensors to equal C/block_size (32/32), got 2}} %0:2 = tosa.row_gather_block_scaled %arg0, %arg1, %arg2, %row_count {block_size = #tosa.block_size} : (tensor<13x21x32xf4E2M1FN>, tensor<13x21x2xf8E8M0FNU>, tensor<13x26xi32>, tensor<1xi32>) -> (tensor<13x52x32xf4E2M1FN>, tensor<13x52x2xf8E8M0FNU>) return %0#0, %0#1 : tensor<13x52x32xf4E2M1FN>, tensor<13x52x2xf8E8M0FNU> } // ----- func.func @test_pad_padding_shape_mismatch(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { %0 = tosa.const_shape {values = dense<1> : tensor<4xindex>} : () -> !tosa.shape<4> %pad_const = "tosa.const"() {values = dense<3.14> : tensor<1xf32>} : () -> tensor<1xf32> // expected-error@+1 {{'tosa.pad' op padding tensor must have 3 * 2 = 6 elements, but got 4}} %1 = tosa.pad %arg0, %0, %pad_const : (tensor<13x21x3xf32>, !tosa.shape<4>, tensor<1xf32>) -> tensor<13x21x3xf32> return %1 : tensor<13x21x3xf32> } // ----- func.func @test_pad_invalid_padding_rank(%arg0: tensor<13x21xf32>) { %0 = tosa.const_shape {values = dense<1> : tensor<6xindex>} : () -> !tosa.shape<6> %pad_const = "tosa.const"() {values = dense<3.14> : tensor<1xf32>} : () -> tensor<1xf32> // expected-error@+1 {{'tosa.pad' op padding tensor must have 2 * 2 = 4 elements, but got 6}} %1 = tosa.pad %arg0, %0, %pad_const : (tensor<13x21xf32>, !tosa.shape<6>, tensor<1xf32>) -> tensor<13x21xf32> return } // ----- func.func @test_pad_output_mismatch(%arg0: tensor<13x21x3xi8>, %arg1: tensor<1xi8>) -> tensor<13x21x3xi8> { %0 = tosa.const_shape {values = dense<[0, 0, 0, 1, 0, 1]> : tensor<6xindex>} : () -> !tosa.shape<6> // expected-error@+1 {{mismatch in output shape at dimension 1: expected 21 + 0 + 1 = 22, but got 21}} %1 = tosa.pad %arg0, %0, %arg1 : (tensor<13x21x3xi8>, !tosa.shape<6>, tensor<1xi8>) -> tensor<13x21x3xi8> return %1 : tensor<13x21x3xi8> } // ----- func.func @test_pad_invalid_padding_value(%arg0: tensor<10xi8>, %arg1: tensor<1xi8>) -> tensor<10xi8> { %0 = tosa.const_shape {values = dense<[-2, 2]> : tensor<2xindex>} : () -> !tosa.shape<2> // expected-error@+1 {{invalid padding values at dimension 0: values must be non-negative or -1 for dynamic padding, got [-2, 2]}} %1 = tosa.pad %arg0, %0, %arg1 : (tensor<10xi8>, !tosa.shape<2>, tensor<1xi8>) -> tensor<10xi8> return %1 : tensor<10xi8> } // ----- func.func @test_cond_if_wrong_terminator_op(%arg0: tensor) -> tensor { %0 = "tosa.cond_if"(%arg0) ({ %1 = "tosa.const"() <{values = dense<1> : tensor}> : () -> tensor "tosa.yield"(%1) : (tensor) -> () }, { // expected-error@+2 {{'func.return' op expects parent op 'func.func'}} %2 = "tosa.const"() <{values = dense<2> : tensor}> : () -> tensor "func.return"(%2) : (tensor) -> () }) : (tensor) -> tensor return %0 : tensor } // ----- func.func @test_cond_if_missing_then_terminator(%arg0: tensor) -> tensor { %0 = "tosa.cond_if"(%arg0) ({ // expected-error@+1 {{block with no terminator}} %1 = "tosa.const"() <{values = dense<1> : tensor}> : () -> tensor }, { %2 = "tosa.const"() <{values = dense<2> : tensor}> : () -> tensor "tosa.yield"(%2) : (tensor) -> () }) : (tensor) -> tensor return %0 : tensor } // ----- func.func @test_cond_if_missing_else_terminator(%arg0: tensor) -> tensor { %0 = "tosa.cond_if"(%arg0) ({ %1 = "tosa.const"() <{values = dense<1> : tensor}> : () -> tensor "tosa.yield"(%1) : (tensor) -> () }, { // expected-error@+1 {{block with no terminator}} %2 = "tosa.const"() <{values = dense<2> : tensor}> : () -> tensor }) : (tensor) -> tensor return %0 : tensor } // ----- func.func @test_cond_if_input_list_mismatch_then_block(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'then_graph' arguments (1) and 'input_list' (2)}} %0 = "tosa.cond_if"(%arg2, %arg0, %arg1) ({ ^bb0(%arg3: tensor): tosa.yield %arg3 : tensor }, { ^bb0(%arg4: tensor): tosa.yield %arg4 : tensor }) : (tensor, tensor, tensor) -> tensor return %0 : tensor } // ----- func.func @test_cond_if_input_list_mismatch_then_block_2(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'then_graph' arguments (2) and 'input_list' (1)}} %0 = "tosa.cond_if"(%arg2, %arg0) ({ ^bb0(%arg3: tensor, %arg4: tensor): tosa.yield %arg3 : tensor }, { ^bb0(%arg4: tensor): tosa.yield %arg4 : tensor }) : (tensor, tensor) -> tensor return %0 : tensor } // ----- func.func @test_cond_if_input_list_mismatch_else_block(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'else_graph' arguments (1) and 'input_list' (2)}} %0 = "tosa.cond_if"(%arg2, %arg0, %arg1) ({ ^bb0(%arg3: tensor, %arg4: tensor): tosa.yield %arg3 : tensor }, { ^bb0(%arg4: tensor): tosa.yield %arg4 : tensor }) : (tensor, tensor, tensor) -> tensor return %0 : tensor } // ----- func.func @test_cond_if_input_list_mismatch_else_block_2(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'else_graph' arguments (2) and 'input_list' (1)}} %0 = "tosa.cond_if"(%arg2, %arg0) ({ ^bb0(%arg3: tensor): tosa.yield %arg3 : tensor }, { ^bb0(%arg4: tensor, %arg3: tensor): tosa.yield %arg4 : tensor }) : (tensor, tensor) -> tensor return %0 : tensor } // ----- func.func @test_cond_if_input_list_mismatch_else_block_simple(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'else_graph' arguments (1) and 'input_list' (2)}} %0 = tosa.cond_if %arg2 (%arg3 = %arg0, %arg4 = %arg1) : tensor (tensor, tensor) -> tensor { ^bb0(%arg3: tensor, %arg4: tensor): %1 = tosa.add %arg3, %arg4 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } else { ^bb0(%arg3: tensor): tosa.yield %arg3 : tensor } return %0 : tensor } // ----- func.func @test_cond_if_input_list_mismatch_else_block_simple_2(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'else_graph' arguments (2) and 'input_list' (1)}} %0 = tosa.cond_if %arg2 (%arg3 = %arg0) : tensor (tensor) -> tensor { ^bb0(%arg3: tensor): tosa.yield %arg3 : tensor } else { ^bb0(%arg3: tensor, %arg4: tensor): %1 = tosa.sub %arg3, %arg4 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } return %0 : tensor } // ----- func.func @test_cond_if_output_list_mismatch_then_block(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'then_graph' results (2) and 'output_list' (1)}} %0 = tosa.cond_if %arg2 : tensor -> tensor { %1 = tosa.add %arg0, %arg1 : (tensor, tensor) -> tensor %2 = tosa.add %1, %arg1 : (tensor, tensor) -> tensor tosa.yield %1, %2 : tensor, tensor } else { %1 = tosa.sub %arg0, %arg1 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } return %0 : tensor } // ----- func.func @test_cond_if_output_list_mismatch_then_block_2(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'then_graph' results (1) and 'output_list' (2)}} %0, %2 = tosa.cond_if %arg2 : tensor -> (tensor, tensor) { %1 = tosa.add %arg0, %arg1 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } else { %1 = tosa.sub %arg0, %arg1 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } return %0 : tensor } // ----- func.func @test_cond_if_output_list_mismatch_else_block(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'else_graph' results (2) and 'output_list' (1)}} %0 = tosa.cond_if %arg2 : tensor -> tensor { %1 = tosa.add %arg0, %arg1 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } else { %1 = tosa.sub %arg0, %arg1 : (tensor, tensor) -> tensor %2 = tosa.add %1, %arg1 : (tensor, tensor) -> tensor tosa.yield %1, %2 : tensor, tensor } return %0 : tensor } // ----- func.func @test_cond_if_output_list_mismatch_else_block_2(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{'tosa.cond_if' op require same number of values in 'else_graph' results (1) and 'output_list' (2)}} %0, %2 = tosa.cond_if %arg2 : tensor -> (tensor, tensor) { %1 = tosa.add %arg0, %arg1 : (tensor, tensor) -> tensor %2 = tosa.sub %arg0, %arg1 : (tensor, tensor) -> tensor tosa.yield %1, %2 : tensor, tensor } else { %1 = tosa.sub %arg0, %arg1 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } return %0 : tensor } // ----- func.func @test_cond_if_cond_input_not_size_one(%arg0: tensor, %arg1: tensor, %arg2: tensor<2xi1>) -> tensor { // expected-error@+1 {{'tosa.cond_if' op 'condition' must be a size 1 tensor, got 'tensor<2xi1>'}} %0 = "tosa.cond_if"(%arg2, %arg0, %arg1) ({ ^bb0(%arg3: tensor, %arg4: tensor): tosa.yield %arg3 : tensor }, { ^bb0(%arg3: tensor, %arg4: tensor): tosa.yield %arg4 : tensor }) : (tensor<2xi1>, tensor, tensor) -> tensor return %0 : tensor } // ----- // CHECK-LABEL: cond_if_cond_type func.func @test_cond_if_cond_type(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+2 {{expected ':'}} // expected-error@+1 {{custom op 'tosa.cond_if' expected type for condition operand}} %0 = tosa.cond_if %arg2 -> (tensor) { tosa.yield %arg0 : tensor } else { tosa.yield %arg1 : tensor } return %0 : tensor } // ----- func.func @test_cond_if_input_list_type_mismatch_simple(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+1 {{custom op 'tosa.cond_if' expected as many input types as operands (expected 2 got 0)}} %0 = tosa.cond_if %arg2 (%arg3 = %arg0, %arg4 = %arg1) : tensor () -> tensor { ^bb0(%arg3: tensor, %arg4: tensor): %1 = tosa.add %arg3, %arg4 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } else { ^bb0(%arg3: tensor, %arg4: tensor): %1 = tosa.sub %arg3, %arg4 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } return %0 : tensor } // ----- func.func @test_cond_if_incorrect_type_simple(%arg0: tensor, %arg1: tensor, %arg2: tensor) -> tensor { // expected-error@+2 {{expected non-function type}} // expected-error@+1 {{custom op 'tosa.cond_if' expected list of types for block arguments followed by arrow type and list of return types}} %0 = tosa.cond_if %arg2 (%arg3 = %arg0, %arg4 = %arg1) : tensor (%arg3) -> tensor { ^bb0(%arg3: tensor, %arg4: tensor): %1 = tosa.add %arg3, %arg4 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } else { ^bb0(%arg3: tensor, %arg4: tensor): %1 = tosa.sub %arg3, %arg4 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } return %0 : tensor } // ----- func.func @test_while_loop_wrong_terminator(%arg0: tensor, %arg1: tensor) -> tensor { %0 = tosa.while_loop (%arg2 = %arg0) : (tensor) -> tensor { // expected-error@+2 {{'func.return' op expects parent op 'func.func'}} %1 = tosa.greater_equal %arg1, %arg2 : (tensor, tensor) -> tensor "func.return"(%arg2) : (tensor) -> () } do { ^bb0(%arg2: tensor): %1 = "tosa.const"() <{values = dense<1> : tensor}> : () -> tensor %2 = tosa.add %arg2, %1 : (tensor, tensor) -> tensor tosa.yield %2 : tensor } return %0 : tensor } // ----- func.func @test_while_loop_missing_cond_terminator(%arg0: tensor, %arg1: tensor) -> tensor { %0 = tosa.while_loop (%arg2 = %arg0) : (tensor) -> tensor { // expected-error@+1 {{block with no terminator}} %1 = tosa.greater_equal %arg1, %arg2 : (tensor, tensor) -> tensor } do { ^bb0(%arg2: tensor): %1 = "tosa.const"() <{values = dense<1> : tensor}> : () -> tensor %2 = tosa.add %arg2, %1 : (tensor, tensor) -> tensor tosa.yield %2 : tensor } return %0 : tensor } // ----- func.func @test_while_loop_missing_body_terminator(%arg0: tensor, %arg1: tensor) -> tensor { %0 = tosa.while_loop (%arg2 = %arg0) : (tensor) -> tensor { %1 = tosa.greater_equal %arg1, %arg2 : (tensor, tensor) -> tensor tosa.yield %1 : tensor } do { ^bb0(%arg2: tensor): // expected-error@+1 {{block with no terminator}} %1 = "tosa.const"() <{values = dense<1> : tensor}> : () -> tensor } return %0 : tensor } // ----- func.func @test_while_loop_input_list_mismatch_body_block_in(%arg0: tensor<10xi32>, %arg1: tensor) { %0 = "tosa.const"() {values = dense<0> : tensor} : () -> tensor // expected-error@+1 {{'tosa.while_loop' op require same number of values in 'body_graph' arguments (3) and 'input_list' (2)}} %1:2 = tosa.while_loop (%arg2 = %0, %arg3 = %arg0) : (tensor, tensor<10xi32>) -> (tensor, tensor<10xi32>) { %2 = tosa.greater_equal %arg2, %arg1 : (tensor, tensor) -> tensor tosa.yield %2 : tensor } do { ^bb0(%arg2: tensor, %arg3: tensor, %arg4: tensor<10xi32>): %2 = "tosa.const"() {values = dense<1> : tensor} : () -> tensor %3 = tosa.add %arg2, %2 : (tensor, tensor) -> tensor tosa.yield %3, %arg4 : tensor, tensor<10xi32> } return } // ----- func.func @test_while_loop_input_list_mismatch_body_block_in_2(%arg0: tensor<10xi32>, %arg1: tensor) { %0 = "tosa.const"() {values = dense<0> : tensor} : () -> tensor // expected-error@+1 {{'tosa.while_loop' op require same number of values in 'body_graph' arguments (2) and 'input_list' (3)}} %1:3 = tosa.while_loop (%arg2 = %0, %arg3 = %arg0, %arg4 = %arg0) : (tensor