8K levels: Tensor op tests kernel/stride at 8192 maximums

Operators updated: AVG_POOL2D, MAX_POOL2D, CONV2D, CONV3D,
 DEPTHWISE_CONV2D & TRANSPOSE_CONV2D
tosa_verif_build_tests argument --level-8k-sizes used to
allow kernel/stride maximum boundary testing

Fixed bugs in height/width validator function meaning some
esixting avg_pool2d float tests need regening.

Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
Change-Id: I7aeab82d3bd3c49d02d54708f2c9d995cd3cf2df

1 files changed, 32 insertions, 46 deletions

diff --git a/verif/generator/tosa_error_if.py b/verif/generator/tosa_error_if.py
index b19d5e9..8c40371 100644
--- a/verif/generator/tosa_error_if.py
+++ b/verif/generator/tosa_error_if.py
@@ -2547,14 +2547,16 @@ class TosaInvalidValidator:
 
         args = kwargs["args"]
 
-        # MaxPool2D has no accum_dtype arg
-        stride_idx, pad_idx = (0, 1) if opName == "max_pool2d" else (1, 2)
+        # Skip accum_dtype arg (apart from MaxPool2D that doesn't have one)
+        stride_idx, pad_idx = (1, 2) if opName != "max_pool2d" else (0, 1)
+
+        # Common info for all ops
         strides = args[stride_idx]
         padding = args[pad_idx]
 
         if opName.endswith("pool2d"):
             # avg_pool2d, max_pool2d
-            kernel_shape = args[2]
+            kernel_shape = args[pad_idx + 1]
             h = (
                 input_shape[1] + padding[0] + padding[1] + strides[0] - kernel_shape[0]
             ) // strides[0]
@@ -2566,53 +2568,36 @@ class TosaInvalidValidator:
 
         if opName.startswith("transpose_conv2d"):
             # transpose_conv2d
-            output_shape = args[2]
+            output_shape = args[pad_idx + 1]
             filter_shape = inputShapes[1]
             kernel_shape = filter_shape[1:-1]
 
             def get_out_size(in_size, stride, kernel_size, out_pad, in_pad):
-                """Calculate the transpose_conv2d output size for a dimension.
-
-                Args:
-                    in_size: the input size - int
-                    stride: the stride - int
-                    kernel_size: the kernel size - int
-                    out_pad: the output padding - int
-                    in_pad: the input padding - int
-
-                Returns:
-                    the output size
-                """
-                return (in_size - 1) * stride + kernel_size - in_pad - out_pad
-
-            for pad_h, pad_w in (
-                (kernel_shape[0] - 1, kernel_shape[1] - 1),  # FULL padding
-                (kernel_shape[0] // 2, kernel_shape[1] // 2),  # SAME padding
-                (0, 0),  # VALID padding
-            ):
-                h = get_out_size(
-                    input_shape[1],
-                    strides[0],
-                    kernel_shape[0],
-                    padding[0],
-                    pad_h,
-                )
-                w = get_out_size(
-                    input_shape[2],
-                    strides[1],
-                    kernel_shape[1],
-                    padding[1],
-                    pad_w,
-                )
-                if output_shape[1] == h and output_shape[2] == w:
-                    return False
-
-            # output shape does not match the expected shape for any padding option
+                """Calculate the transpose_conv2d output size for a dimension."""
+                return (in_size - 1) * stride + kernel_size + in_pad + out_pad
+
+            h = get_out_size(
+                input_shape[1],
+                strides[0],
+                kernel_shape[0],
+                padding[0],
+                padding[1],
+            )
+            w = get_out_size(
+                input_shape[2],
+                strides[1],
+                kernel_shape[1],
+                padding[2],
+                padding[3],
+            )
+            if output_shape[1] == h and output_shape[2] == w:
+                return False
+            # output shape does not match the expected shape
             return True
 
         if "conv2d" in opName or "conv3d" in opName:
             # conv2d, conv3d, depthwise_conv2d
-            dilations = args[2]
+            dilations = args[pad_idx + 1]
             filter_shape = inputShapes[1]
             kernel_shape = (
                 filter_shape[0:2]
@@ -2621,12 +2606,13 @@ class TosaInvalidValidator:
             )
 
             for i in range(len(kernel_shape)):
+                pad_offset = i * 2
                 dim = (
                     input_shape[i + 1]
-                    - kernel_shape[i]
-                    - (kernel_shape[i] - 1) * (dilations[i] - 1)
-                    + padding[i * 2 + 0]
-                    + padding[i * 2 + 1]
+                    - 1
+                    + padding[pad_offset]
+                    + padding[pad_offset + 1]
+                    - (kernel_shape[i] - 1) * dilations[i]
                 ) // strides[i] + 1
                 # return True if any dimension is < 1
                 if dim < 1: