diff options
Diffstat (limited to 'verif/generator/tosa_arg_gen.py')
| -rw-r--r-- | verif/generator/tosa_arg_gen.py | 39 |
1 files changed, 11 insertions, 28 deletions
diff --git a/verif/generator/tosa_arg_gen.py b/verif/generator/tosa_arg_gen.py index 370570c..75ca634 100644 --- a/verif/generator/tosa_arg_gen.py +++ b/verif/generator/tosa_arg_gen.py @@ -192,10 +192,7 @@ class TosaTensorGen: assert rank == 4 shape = testGen.makeShape(rank) - - # Constrict the batch size? - if testGen.args.max_batch_size: - shape[0] = (shape[0] % testGen.args.max_batch_size) + 1 + shape = testGen.constrictBatchSize(shape) # Constrict the overall size of the shape when creating ERROR_IF tests if error_name and error_name != ErrorIf.MaxDimExceeded: @@ -220,7 +217,7 @@ class TosaTensorGen: # ignore max batch size if target shape is set if testGen.args.max_batch_size and not testGen.args.target_shapes: - values_in_shape[0] = (values_in_shape[0] % testGen.args.max_batch_size) + 1 + values_in_shape[0] = min(values_in_shape[0], testGen.args.max_batch_size) W = testGen.randInt( testGen.args.tensor_shape_range[0], testGen.args.tensor_shape_range[1] @@ -282,10 +279,7 @@ class TosaTensorGen: # IFM dimensions are NHWC ifm_shape = testGen.makeShape(rank) - - # Constrict the batch size? - if testGen.args.max_batch_size: - ifm_shape[0] = (ifm_shape[0] % testGen.args.max_batch_size) + 1 + ifm_shape = testGen.constrictBatchSize(ifm_shape) # Constrict the overall size of the shape when creating ERROR_IF tests if error_name: @@ -297,7 +291,7 @@ class TosaTensorGen: filter_hw = op["filter"] # Generate a random OFM depth - ofm_depth = testGen.makeShape(1)[0] + ofm_depth = testGen.makeDimension() # The filter dimensions are OHWI filter_shape = np.asarray([ofm_depth, filter_hw[0], filter_hw[1], ifm_shape[3]]) @@ -316,10 +310,7 @@ class TosaTensorGen: # IFM dimensions are NDHWC ifm_shape = testGen.makeShape(rank) - - # Constrict the batch size? - if testGen.args.max_batch_size: - ifm_shape[0] = (ifm_shape[0] % testGen.args.max_batch_size) + 1 + ifm_shape = testGen.constrictBatchSize(ifm_shape) # Constrict the overall size of the shape when creating ERROR_IF tests if error_name: @@ -331,7 +322,7 @@ class TosaTensorGen: filter_dhw = op["filter"] # Generate a random OFM channel - ofm_channel = testGen.makeShape(1)[0] + ofm_channel = testGen.makeDimension() # The filter dimensions are ODHWI filter_shape = np.asarray( @@ -352,10 +343,7 @@ class TosaTensorGen: # IFM dimensions are NHWC ifm_shape = testGen.makeShape(rank) - - # Constrict the batch size? - if testGen.args.max_batch_size: - ifm_shape[0] = (ifm_shape[0] % testGen.args.max_batch_size) + 1 + ifm_shape = testGen.constrictBatchSize(ifm_shape) # Constrict the overall size of the shape when creating ERROR_IF tests if error_name: @@ -367,7 +355,7 @@ class TosaTensorGen: filter_hw = op["filter"] # Generate a random OFM depth - ofm_depth = testGen.makeShape(1)[0] + ofm_depth = testGen.makeDimension() # The filter dimensions are OHWI filter_shape = np.asarray([ofm_depth, filter_hw[0], filter_hw[1], ifm_shape[3]]) @@ -387,10 +375,7 @@ class TosaTensorGen: # IFM dimensions are NHWC ifm_shape = testGen.makeShape(rank) - - # Constrict the batch size? - if testGen.args.max_batch_size: - ifm_shape[0] = (ifm_shape[0] % testGen.args.max_batch_size) + 1 + ifm_shape = testGen.constrictBatchSize(ifm_shape) # Constrict the overall size of the shape when creating ERROR_IF tests if error_name: @@ -405,7 +390,7 @@ class TosaTensorGen: # Generate a random OFM depth, but don't let it get too big because # the output depth is M * C filter_m = ( - testGen.makeShape(1)[0] % (testGen.args.tensor_shape_range[1] // 4) + testGen.makeDimension() % (testGen.args.tensor_shape_range[1] // 4) ) + 1 # The filter dimensions are HWCM @@ -484,9 +469,7 @@ class TosaTensorGen: ifm_shape[1] += selected_inc[0] ifm_shape[2] += selected_inc[1] - # Constrict the batch size - if testGen.args.max_batch_size: - ifm_shape[0] = (ifm_shape[0] % testGen.args.max_batch_size) + 1 + ifm_shape = testGen.constrictBatchSize(ifm_shape) return [ifm_shape] |