1 files changed, 51 insertions, 0 deletions
diff --git a/tests/nnapi/specs/V1_1/space_to_batch_quant8_2_nnfw.mod.py b/tests/nnapi/specs/V1_1/space_to_batch_quant8_2_nnfw.mod.py
new file mode 100644
index 000000000..47b721a6c
--- /dev/null
+++ b/tests/nnapi/specs/V1_1/space_to_batch_quant8_2_nnfw.mod.py
@@ -0,0 +1,51 @@
+batch = 2
+rows = 3
+cols = 4
+depth = 5
+block_size_height = 2
+block_size_width = 3
+padding_size_height_top = 1
+padding_size_height_bottom = 2
+padding_size_width_left = 3
+padding_size_width_right = 2
+zero_value = 200
+scale = 1.0
+out_batch = batch * block_size_height * block_size_width
+out_rows = (int)((rows + padding_size_height_top + padding_size_height_bottom) / block_size_height)
+out_cols = (int)((cols + padding_size_width_left + padding_size_width_right) / block_size_width)
+
+input_table = [x for x in range(batch * rows * cols * depth)]
+
+output_table = [x for x in range(out_batch * out_rows * out_cols * depth)]
+for b in range(batch):
+  for h in range(rows + padding_size_height_top + padding_size_height_bottom):
+    for w in range(cols + padding_size_width_left + padding_size_width_right):
+      for d in range(depth):
+        out_d = d;
+        out_h = (int)(h / block_size_height);
+        out_w = (int)(w / block_size_width);
+        out_b = b + ((h % block_size_height) * block_size_width + w % block_size_width) * batch;
+
+        if (h < padding_size_height_top) or (h >= (rows + padding_size_height_top)) or (w < padding_size_width_left) or (w >= (cols + padding_size_width_left)):
+          output_table[out_b * out_rows * out_cols * depth + out_h * out_cols * depth + out_w * depth + out_d] = zero_value;
+        else:
+          output_table[out_b * out_rows * out_cols * depth + out_h * out_cols * depth + out_w * depth + out_d] = input_table[b * rows * cols * depth + (h - padding_size_height_top) * cols * depth + (w - padding_size_width_left) * depth + d];
+
+i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, %d, %d" % (batch, rows, cols, depth, scale, zero_value))
+block = Parameter("block_size", "TENSOR_INT32", "{2}", [block_size_height, block_size_width])
+paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [padding_size_height_top, padding_size_height_bottom, padding_size_width_left, padding_size_width_right])
+output = Output("output", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, %d, %d" % (out_batch, out_rows, out_cols, depth, scale, zero_value))
+
+model = Model()
+model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
+
+
+# Example 1. Input in operand 0,
+input0 = {i1: # input 0
+          input_table}
+
+output0 = {output: # output 0
+          output_table}
+
+# Instantiate an example
+Example((input0, output0))