Update tensor ops ERROR_IF criteria
Update to ref model to check ERROR_IF criteria for pooling
and convolution ops to match specification
Update to tosa_verif_build_tests to produce valid test ranges and
new ERROR_IF tests
Plus update pooling ops big kernel to 9 (from 6) for better testing
coverage and set dilation to 1 and add out_pad bottom & right for
transpose_conv2d to match specification
Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
Change-Id: Ic5759872d40ae8d3f3d07043d9a0f2fa0244d72e
diff --git a/reference_model/src/ops/tensor_ops.cc b/reference_model/src/ops/tensor_ops.cc
index 02fdf01..4a56093 100644
--- a/reference_model/src/ops/tensor_ops.cc
+++ b/reference_model/src/ops/tensor_ops.cc
@@ -92,10 +92,22 @@
return 1;
}
- if ((OH != (IH + pad_top + pad_bottom + stride_y - kernel_y) / stride_y) ||
- (OW != (IW + pad_left + pad_right + stride_x - kernel_x) / stride_x))
+ int32_t full_H = IH + pad_top + pad_bottom - kernel_y;
+ int32_t full_W = IW + pad_left + pad_right - kernel_x;
+
+ if ((full_H % stride_y != 0) ||
+ (full_W % stride_x != 0))
{
- msg = "Mismatch between output shape provided and expected output shape";
+ msg = "Parameters must yield exact integer output dimensions";
+ return 1;
+ }
+
+ if ((OH != (full_H / stride_y) + 1) ||
+ (OW != (full_W / stride_x) + 1))
+ {
+ msg = "Mismatch between output shape provided and expected output shape (" +
+ std::to_string((full_H / stride_y) + 1) + "," +
+ std::to_string((full_W / stride_x) + 1) + ")";
return 1;
}
@@ -107,6 +119,8 @@
uint32_t conv_dimension,
std::vector<int32_t> input_shape,
std::vector<int32_t> output_shape,
+ std::vector<int32_t> weights,
+ uint32_t offset_kernel,
DType InDtype,
DType WeightDtype,
std::string& msg)
@@ -156,6 +170,62 @@
}
}
+ ASSERT_MSG(conv_dimension == 2 || conv_dimension == 3, "Unsupported convolution dimension")
+
+ int32_t offset_d = 1 ? conv_dimension == 3 : 0;
+ int32_t ID = conv_dimension == 3 ? input_shape[1] : 1;
+ int32_t IH = input_shape[1 + offset_d];
+ int32_t IW = input_shape[2 + offset_d];
+ int32_t OD = conv_dimension == 3 ? output_shape[1] : 1;
+ int32_t OH = output_shape[1 + offset_d];
+ int32_t OW = output_shape[2 + offset_d];
+
+ int32_t stride_d = conv_dimension == 3 ? attribute->stride()[0] : 1;
+ int32_t stride_y = attribute->stride()[0 + offset_d];
+ int32_t stride_x = attribute->stride()[1 + offset_d];
+ int32_t kernel_d = conv_dimension == 3 ? weights[offset_kernel] : 1;
+ int32_t kernel_h = weights[offset_kernel + offset_d];
+ int32_t kernel_w = weights[offset_kernel + 1 + offset_d];
+ int32_t dilation_d = conv_dimension == 3 ? attribute->dilation()[0] : 1;
+ int32_t dilation_y = attribute->dilation()[0 + offset_d];
+ int32_t dilation_x = attribute->dilation()[1 + offset_d];
+
+ offset_d *= 2;
+ int32_t pad_d0 = conv_dimension == 3 ? attribute->padding()[0] : 0;
+ int32_t pad_d1 = conv_dimension == 3 ? attribute->padding()[1] : 0;
+ int32_t pad_top = attribute->padding()[0 + offset_d];
+ int32_t pad_bottom = attribute->padding()[1 + offset_d];
+ int32_t pad_left = attribute->padding()[2 + offset_d];
+ int32_t pad_right = attribute->padding()[3 + offset_d];
+
+ int32_t full_D = ID - 1 + pad_d0 + pad_d1 - (kernel_d - 1) * dilation_d;
+ int32_t full_H = IH - 1 + pad_top + pad_bottom - (kernel_h - 1) * dilation_y;
+ int32_t full_W = IW - 1 + pad_left + pad_right - (kernel_w - 1) * dilation_x;
+
+ if ((full_H % stride_y != 0) ||
+ (full_W % stride_x != 0) ||
+ (full_D % stride_d != 0))
+ {
+ msg = "Parameters must yield exact integer output dimensions";
+ return 1;
+ }
+
+ if ((OH != (full_H / stride_y) + 1) ||
+ (OW != (full_W / stride_x) + 1) ||
+ (OD != (full_D / stride_d) + 1))
+ {
+ std::string msg_d = "";
+ if (conv_dimension == 3)
+ {
+ msg_d += std::to_string((full_D / stride_d) + 1) + ",";
+ }
+ msg = "Mismatch between output shape provided and expected output shape (" +
+ msg_d +
+ std::to_string((full_H / stride_y) + 1) + "," +
+ std::to_string((full_W / stride_x) + 1) + ")";
+ return 1;
+ }
+
if (qinfo)
{
if (InDtype != DType_INT8 && qinfo->input_zp() != 0)
@@ -529,7 +599,7 @@
std::string msg;
if (check_conv_attribute_qinfo(attribute, qinfo, 2 /* conv_dimension */, input->getShape(), output->getShape(),
- InDtype, WeightDtype, msg))
+ weight->getShape(), 1 /* offset_kernel */, InDtype, WeightDtype, msg))
{
msg = "OpConv2d: " + msg;
printNodeValidationError(msg.c_str());
@@ -715,7 +785,7 @@
std::string msg;
if (check_conv_attribute_qinfo(attribute, qinfo, 3 /* conv_dimension */, input->getShape(), output->getShape(),
- InDtype, WeightDtype, msg))
+ weight->getShape(), 1 /* offset_kernel */, InDtype, WeightDtype, msg))
{
msg = "OpConv3d: " + msg;
printNodeValidationError(msg.c_str());
@@ -904,7 +974,7 @@
std::string msg;
if (check_conv_attribute_qinfo(attribute, qinfo, 2 /* conv_dimension */, input->getShape(), output->getShape(),
- InDtype, WeightDtype, msg))
+ weight->getShape(), 0 /* offset_kernel */, InDtype, WeightDtype, msg))
{
msg = "OpDepthwiseConv2d: " + msg;
printNodeValidationError(msg.c_str());
@@ -1447,7 +1517,7 @@
bias = dynamic_cast<TosaReference::TensorTemplate<TBias>*>(inputs[2]);
output = dynamic_cast<TosaReference::TensorTemplate<TAcc>*>(outputs[0]);
- if (attribute->outpad().size() != 2)
+ if (attribute->outpad().size() != 4)
{
printNodeValidationError("OpTransposeConv2d: illegal size for attribute outpad");
return 1;
@@ -1489,11 +1559,12 @@
}
}
+ // TODO: Remove dilation once schema updated
for (int32_t i : attribute->dilation())
{
- if (i < 1)
+ if (i != 1)
{
- printNodeValidationError("OpTransposeConv2d: At least one dilation is smaller than one");
+ printNodeValidationError("OpTransposeConv2d: Dilation is deprecated and must be set to one");
return 1;
}
}
@@ -1507,6 +1578,33 @@
}
}
+ int32_t IH = input->getShape()[1];
+ int32_t IW = input->getShape()[2];
+ int32_t OH = output->getShape()[1];
+ int32_t OW = output->getShape()[2];
+
+ int32_t stride_y = attribute->stride()[0];
+ int32_t stride_x = attribute->stride()[1];
+ int32_t kernel_h = weight->getShape()[1];
+ int32_t kernel_w = weight->getShape()[2];
+
+ int32_t outpad_top = attribute->outpad()[0];
+ int32_t outpad_bottom = attribute->outpad()[1];
+ int32_t outpad_left = attribute->outpad()[2];
+ int32_t outpad_right = attribute->outpad()[3];
+
+ int32_t H = (IH - 1) * stride_y - outpad_top - outpad_bottom + kernel_h;
+ int32_t W = (IW - 1) * stride_x - outpad_left - outpad_right + kernel_w;
+
+ if ((OH != H) || (OW != W))
+ {
+ std::string msg = "OpTransposeConv2d: Mismatch between output shape provided and expected output shape (" +
+ std::to_string(H) + "," +
+ std::to_string(W) + ")";
+ printNodeValidationError(msg.c_str());
+ return 1;
+ }
+
if (this->qinfo)
{
if (InDtype != DType_INT8)
@@ -1542,12 +1640,13 @@
int out_width = this->output->getShape()[2];
int out_channels = this->output->getShape()[3];
- int padding_top = this->attribute->outpad()[0];
- int padding_left = this->attribute->outpad()[1];
- int stride_h = this->attribute->stride()[0];
- int stride_w = this->attribute->stride()[1];
- int dilation_h = this->attribute->dilation()[0];
- int dilation_w = this->attribute->dilation()[1];
+ int outpad_top = this->attribute->outpad()[0];
+ int outpad_bottom = this->attribute->outpad()[1];
+ int outpad_left = this->attribute->outpad()[2];
+ int outpad_right = this->attribute->outpad()[3];
+
+ int stride_h = this->attribute->stride()[0];
+ int stride_w = this->attribute->stride()[1];
ERROR_IF(in_batch != out_batch, "OpTransposeConv2d: tensor batch mismatch %d != %d", in_batch, out_batch);
ERROR_IF(f_in_channels != in_channels, "OpTransposeConv2d: tensor input channel mismatch %d != %d", f_in_channels,
@@ -1559,10 +1658,10 @@
DEBUG_INFO(OP,
"perform OpTransposeConv2d, input.shape=[%d,%d,%d,%d], weight.shape=[%d,%d,%d,%d], "
- "output.shape=[%d,%d,%d,%d], stride=[%d,%d], dilation=[%d,%d], padding=[%d,%d]",
- in_batch, in_height, in_width, in_channels, f_height, f_width, f_out_channels, f_in_channels, out_batch,
- out_height, out_width, out_channels, stride_h, stride_w, dilation_h, dilation_w, padding_top,
- padding_left);
+ "output.shape=[%d,%d,%d,%d], stride=[%d,%d], outpad=[%d,%d,%d,%d]",
+ in_batch, in_height, in_width, in_channels, f_height, f_width, f_out_channels, f_in_channels,
+ out_batch, out_height, out_width, out_channels, stride_h, stride_w, outpad_top,
+ outpad_bottom, outpad_left, outpad_right);
TIn input_val = this->input->getTensor();
TWeight weight_val = this->weight->getTensor();
@@ -1595,16 +1694,16 @@
{
for (int iw = 0; iw < in_width; iw++)
{
- out_x_origin = iw * stride_w - padding_left;
- out_y_origin = ih * stride_h - padding_top;
+ out_x_origin = iw * stride_w - outpad_left;
+ out_y_origin = ih * stride_h - outpad_top;
for (int ic = 0; ic < in_channels; ic++)
{
for (int fh = 0; fh < f_height; fh++)
{
for (int fw = 0; fw < f_width; fw++)
{
- out_x = out_x_origin + fw * dilation_w;
- out_y = out_y_origin + fh * dilation_h;
+ out_x = out_x_origin + fw;
+ out_y = out_y_origin + fh;
for (int oc = 0; oc < out_channels; oc++)
{
if ((out_x >= 0 && out_x < out_width) && (out_y >= 0 && out_y < out_height))