diff options
Diffstat (limited to 'verif/generator/tosa_arg_gen.py')
| -rw-r--r-- | verif/generator/tosa_arg_gen.py | 112 |
1 files changed, 87 insertions, 25 deletions
diff --git a/verif/generator/tosa_arg_gen.py b/verif/generator/tosa_arg_gen.py index ffa3683..4878708 100644 --- a/verif/generator/tosa_arg_gen.py +++ b/verif/generator/tosa_arg_gen.py @@ -1976,6 +1976,9 @@ class TosaArgGen: sparsity += 1 return sparsity + # Maximum number of error_if variants to produce + MAX_CONV_ERROR_IFS = 3 + @staticmethod def agConv(testGen, rng, opName, shapeList, dtypes, error_name=None): # Used by CONV2D, CONV3D and DEPTHWISE_CONV2D @@ -2017,17 +2020,60 @@ class TosaArgGen: k_size *= ifm_shape[-1] if not testGen.args.level8k: - # Generate comprehensive argument lists - # - except for named errors, which use specific invalid value(s) - if error_name == ErrorIf.PadSmallerZero: - p_vals = [rng.choice(range(-5, 0))] + if error_name in ( + ErrorIf.PadSmallerZero, + ErrorIf.StrideSmallerOne, + ErrorIf.DilationSmallerOne, + ): + # Use specific invalid value(s) + if error_name == ErrorIf.PadSmallerZero: + # Create negative paddings but with positive opposite paddings + neg_pad = rng.choice(range(-5, 0)) + p_vals = [neg_pad, abs(neg_pad)] + else: + p_vals = [0, 0] + if error_name == ErrorIf.StrideSmallerOne: + # Can't use stride=0, as it is used to derive output shape, as a divisor + s_vals = [rng.choice(range(-5, 0))] + else: + s_vals = [1] + if error_name == ErrorIf.DilationSmallerOne: + d_vals = [rng.choice(range(-5, 1))] + else: + d_vals = [1] + p = p_vals * k_rank + s = s_vals * k_rank + d = d_vals * k_rank + + # Fix values to produce valid error_if + for index in range(k_rank): + pad_offset = index * 2 + fixed = False + while not fixed: + partial = ( + ifm_shape[index + 1] + - 1 + + p[pad_offset] + + p[pad_offset + 1] + - (k_shape[index] - 1) * d[index] + ) + remainder = partial % s[index] + if partial <= 0: + p[pad_offset + 1] += abs(partial) + 1 + elif remainder: + # Stride will be negative for StrideSmallerOne + assert remainder < 0 + p[pad_offset + 1] += abs(remainder) + else: + fixed = True + paddings = {tuple(p)} + strides = {tuple(s)} + dilations = {tuple(d)} + logger.debug(f"agConv: error pad={p} stride={s} dilation={d}") else: + # Generate comprehensive argument lists p_vals = [x for x in range(0, testGen.args.max_conv_padding + 1)] - paddings = {x for x in itertools.product(*([p_vals] * k_rank * 2))} - if error_name == ErrorIf.StrideSmallerOne: - # Can't use stride=0, as it is used to derive output shape, as a divisor - s_vals = [rng.choice(range(-5, 0))] - else: + paddings = {x for x in itertools.product(*([p_vals] * k_rank * 2))} # Stride must be greater than 1 to force non-integer error startStride = ( 1 if error_name != ErrorIf.ConvOutputShapeNonInteger else 2 @@ -2035,12 +2081,10 @@ class TosaArgGen: s_vals = [ x for x in range(startStride, testGen.args.max_conv_stride + 1) ] - strides = {x for x in itertools.product(*([s_vals] * k_rank))} - if error_name == ErrorIf.DilationSmallerOne: - d_vals = [rng.choice(range(-5, 1))] - else: d_vals = [x for x in range(1, testGen.args.max_conv_dilation + 1)] - dilations = {x for x in itertools.product(*([d_vals] * k_rank))} + + strides = {x for x in itertools.product(*([s_vals] * k_rank))} + dilations = {x for x in itertools.product(*([d_vals] * k_rank))} if not error_name and testGen.args.oversize: # add some oversize argument values @@ -2064,12 +2108,15 @@ class TosaArgGen: ) max_dim_size = None - # There are too many parameter combinations, so generate them sparsely, - # very sparse for negative tests - sparsity_factor = 2 if error_name else 120 - sparsity = TosaArgGen._calculate_sparsity( - len(paddings) * len(strides) * len(dilations), sparsity_factor - ) + if error_name: + # Cycle through all error_if tests but we only keep the first few + sparsity = 1 + else: + # There are too many parameter combinations, so generate them sparsely, + sparsity_factor = 120 + sparsity = TosaArgGen._calculate_sparsity( + len(paddings) * len(strides) * len(dilations), sparsity_factor + ) else: # Only test 8k levels boundaries bigStride = testGen.TOSA_8K_LEVEL_MAX_STRIDE @@ -2114,13 +2161,15 @@ class TosaArgGen: # Currently allow all combinations that are reasonable size sparsity = 1 + more_tests = True n = 0 for a in accum_dtypes: for s in sorted(list(strides)): for p in sorted(list(paddings)): for d in sorted(list(dilations)): if ( - n % sparsity == 0 + more_tests + and n % sparsity == 0 # the padded shape must exceed the dilation * kernel to get a positive # sized output shape and (ifm_shape[1] - 1 + p[0] + p[1]) @@ -2199,6 +2248,15 @@ class TosaArgGen: args_dict, ) ) + if ( + error_name + and len(arg_list) >= TosaArgGen.MAX_CONV_ERROR_IFS + ): + # Found enough errors + logger.debug( + f"Skipping creating more conv error tests for {error_name}" + ) + more_tests = False n += 1 arg_list = TosaArgGen._add_data_generators( @@ -2482,7 +2540,9 @@ class TosaArgGen: pad_const_int = 0 pad_const_fp = rng.randNumberDType(dtype) else: - return [] + assert error_name == ErrorIf.WrongInputType + pad_const_int = 0 + pad_const_fp = 0 list_shape_pad_values = list(shape_pad_values) # If we are producing tests for rank 6 or greater use sparsity @@ -2523,7 +2583,9 @@ class TosaArgGen: arg_list.append((name, args_dict)) if error_name == ErrorIf.PadSmallerZero and len(arg_list) == 0: - logger.info(f"No ErrorIf test created for input shape: {shapeList[0]}") + logger.debug( + f"agPad: No PadSmallerZero ErrorIf test created for input shape: {shapeList[0]}" + ) arg_list = TosaArgGen._add_data_generators( testGen, @@ -3106,8 +3168,8 @@ class TosaArgGen: # Find new shapes up to the number of permutations asked for # This code is NOT fast. Fortunately, the numbers are fairly small. for p in range(testGen.args.num_rand_permutations): - # Rank from 1 to TOSA_TENSOR_MAX_RANK - newRank = rng.randInt(1, (testGen.TOSA_TENSOR_MAX_RANK + 1)) + # Rank from 1 to MAX_TENSOR_RANK + newRank = rng.randInt(1, (gtu.MAX_TENSOR_RANK + 1)) if len(factors) < newRank: continue |