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merged 3 commits into from
Aug 28, 2025
Merged

Changes to accomodate horizontal padding #63

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480eb53
_calc_memory_bytes_FBP3d_tomobar modifications
dkazanc Aug 18, 2025
f73d053
modifications of the estimators for recon methods and tests updated
dkazanc Aug 18, 2025
3da3464
corrections to logpolar estimator
dkazanc Aug 19, 2025
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63 changes: 42 additions & 21 deletions ...kends/methods_database/packages/backends/httomolibgpu/supporting_funcs/recon/algorithm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -77,12 +77,17 @@ def _calc_memory_bytes_FBP3d_tomobar(
dtype: np.dtype,
**kwargs,
) -> Tuple[int, int]:
det_height = non_slice_dims_shape[0]
det_width = non_slice_dims_shape[1]
if "detector_pad" in kwargs:
detector_pad = kwargs["detector_pad"]
else:
detector_pad = 0

angles_tot = non_slice_dims_shape[0]
det_width = non_slice_dims_shape[1] + 2 * detector_pad
SLICES = 200 # dummy multiplier+divisor to pass large batch size threshold

# 1. input
input_slice_size = np.prod(non_slice_dims_shape) * dtype.itemsize
input_slice_size = (angles_tot * det_width) * dtype.itemsize

########## FFT / filter / IFFT (filtersync_cupy)

Expand All @@ -91,13 +96,13 @@ def _calc_memory_bytes_FBP3d_tomobar(
cufft_estimate_1d(
nx=det_width,
fft_type=CufftType.CUFFT_R2C,
batch=det_height * SLICES,
batch=angles_tot * SLICES,
)
/ SLICES
)

# 3. RFFT output size (proj_f in code)
proj_f_slice = det_height * (det_width // 2 + 1) * np.complex64().itemsize
proj_f_slice = angles_tot * (det_width // 2 + 1) * np.complex64().itemsize

# 4. Filter size (independent of number of slices)
filter_size = (det_width // 2 + 1) * np.float32().itemsize
Expand All @@ -107,7 +112,7 @@ def _calc_memory_bytes_FBP3d_tomobar(
cufft_estimate_1d(
nx=det_width,
fft_type=CufftType.CUFFT_C2R,
batch=det_height * SLICES,
batch=angles_tot * SLICES,
)
/ SLICES
)
Expand All @@ -123,9 +128,7 @@ def _calc_memory_bytes_FBP3d_tomobar(

# 6. we swap the axes before passing data to Astra in ToMoBAR
# https://github.com/dkazanc/ToMoBAR/blob/54137829b6326406e09f6ef9c95eb35c213838a7/tomobar/methodsDIR_CuPy.py#L135
pre_astra_input_swapaxis_slice = (
np.prod(non_slice_dims_shape) * np.float32().itemsize
)
pre_astra_input_swapaxis_slice = (angles_tot * det_width) * np.float32().itemsize

# 7. astra backprojection will generate an output array
# https://github.com/dkazanc/ToMoBAR/blob/54137829b6326406e09f6ef9c95eb35c213838a7/tomobar/astra_wrappers/astra_base.py#L524
Expand All @@ -151,7 +154,7 @@ def _calc_memory_bytes_FBP3d_tomobar(
# so it does not add to the memory overall

# We assume for safety here that one FFT plan is not freed and one is freed
tot_memory_bytes = (
tot_memory_bytes = int(
projection_mem_size + filtersync_size - ifftplan_slice_size + recon_output_size
)

Expand All @@ -166,8 +169,14 @@ def _calc_memory_bytes_LPRec3d_tomobar(
) -> Tuple[int, int]:
# Based on: https://github.com/dkazanc/ToMoBAR/pull/112/commits/4704ecdc6ded3dd5ec0583c2008aa104f30a8a39

if "detector_pad" in kwargs:
detector_pad = kwargs["detector_pad"]
else:
detector_pad = 0

angles_tot = non_slice_dims_shape[0]
DetectorsLengthH = non_slice_dims_shape[1]
DetectorsLengthH_prepad = non_slice_dims_shape[1]
DetectorsLengthH = non_slice_dims_shape[1] + 2 * detector_pad
SLICES = 200 # dummy multiplier+divisor to pass large batch size threshold
_CENTER_SIZE_MIN = 192 # must be divisible by 8

Expand Down Expand Up @@ -210,7 +219,7 @@ def _calc_memory_bytes_LPRec3d_tomobar(
if odd_horiz:
output_dims = tuple(x + 1 for x in output_dims)

in_slice_size = np.prod(non_slice_dims_shape) * dtype.itemsize
in_slice_size = (angles_tot * DetectorsLengthH) * dtype.itemsize
padded_in_slice_size = angles_tot * n * np.float32().itemsize

theta_size = angles_tot * np.float32().itemsize
Expand Down Expand Up @@ -256,7 +265,9 @@ def _calc_memory_bytes_LPRec3d_tomobar(
center_size * center_size * (1 + angle_range_pi_count * 2) * np.int16().itemsize
)

recon_output_size = DetectorsLengthH * DetectorsLengthH * np.float32().itemsize
recon_output_size = (
DetectorsLengthH_prepad * DetectorsLengthH_prepad * np.float32().itemsize
)
ifft2_plan_slice_size = (
cufft_estimate_2d(
nx=(2 * m + 2 * n), ny=(2 * m + 2 * n), fft_type=CufftType.CUFFT_C2C
Expand Down Expand Up @@ -342,24 +353,28 @@ def add_to_memory_counters(amount, per_slice: bool):
add_to_memory_counters(after_recon_swapaxis_slice, True)

return (tot_memory_bytes * 1.05, fixed_amount + 250 * 1024 * 1024)
# return (tot_memory_bytes, fixed_amount)


def _calc_memory_bytes_SIRT3d_tomobar(
non_slice_dims_shape: Tuple[int, int],
dtype: np.dtype,
**kwargs,
) -> Tuple[int, int]:
DetectorsLengthH = non_slice_dims_shape[1]

if "detector_pad" in kwargs:
detector_pad = kwargs["detector_pad"]
else:
detector_pad = 0
anglesnum = non_slice_dims_shape[0]
DetectorsLengthH = non_slice_dims_shape[1] + 2 * detector_pad
# calculate the output shape
output_dims = _calc_output_dim_SIRT3d_tomobar(non_slice_dims_shape, **kwargs)

in_data_size = np.prod(non_slice_dims_shape) * dtype.itemsize
in_data_size = (anglesnum * DetectorsLengthH) * dtype.itemsize
out_data_size = np.prod(output_dims) * dtype.itemsize

astra_projection = 2.5 * (in_data_size + out_data_size)

tot_memory_bytes = 2 * in_data_size + 2 * out_data_size + astra_projection
tot_memory_bytes = int(2 * in_data_size + 2 * out_data_size + astra_projection)
return (tot_memory_bytes, 0)


Expand All @@ -368,14 +383,20 @@ def _calc_memory_bytes_CGLS3d_tomobar(
dtype: np.dtype,
**kwargs,
) -> Tuple[int, int]:
DetectorsLengthH = non_slice_dims_shape[1]
if "detector_pad" in kwargs:
detector_pad = kwargs["detector_pad"]
else:
detector_pad = 0

anglesnum = non_slice_dims_shape[0]
DetectorsLengthH = non_slice_dims_shape[1] + 2 * detector_pad
# calculate the output shape
output_dims = _calc_output_dim_CGLS3d_tomobar(non_slice_dims_shape, **kwargs)

in_data_size = np.prod(non_slice_dims_shape) * dtype.itemsize
in_data_size = (anglesnum * DetectorsLengthH) * dtype.itemsize
out_data_size = np.prod(output_dims) * dtype.itemsize

astra_projection = 2.5 * (in_data_size + out_data_size)

tot_memory_bytes = 2 * in_data_size + 2 * out_data_size + astra_projection
tot_memory_bytes = int(2 * in_data_size + 2 * out_data_size + astra_projection)
return (tot_memory_bytes, 0)
77 changes: 56 additions & 21 deletions tests/test_httomolibgpu.py
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Original file line number Diff line number Diff line change
Expand Up @@ -528,17 +528,24 @@ def test_data_sampler_memoryhook(slices, newshape, interpolation, ensure_clean_m


@pytest.mark.cupy
@pytest.mark.parametrize("padding_detx", [0, 10, 100, 200])
@pytest.mark.parametrize("projections", [1801, 3601])
@pytest.mark.parametrize("slices", [7, 11, 15])
@pytest.mark.parametrize("detectorX", [1200, 2560])
def test_recon_FBP3d_tomobar_memoryhook(
slices, detectorX, projections, ensure_clean_memory, mocker: MockerFixture
slices,
detectorX,
projections,
padding_detx,
ensure_clean_memory,
mocker: MockerFixture,
):
data = cp.random.random_sample((projections, slices, detectorX), dtype=np.float32)
kwargs = {}
kwargs["angles"] = np.linspace(
0.0 * np.pi / 180.0, 180.0 * np.pi / 180.0, data.shape[0]
)
kwargs["detector_pad"] = padding_detx
kwargs["center"] = 500
kwargs["recon_size"] = detectorX
kwargs["recon_mask_radius"] = 0.8
Expand Down Expand Up @@ -579,61 +586,88 @@ def test_recon_FBP3d_tomobar_memoryhook(


@pytest.mark.cupy
# @pytest.mark.parametrize("projections", [1801])
# @pytest.mark.parametrize("detX_size", [2560])
# @pytest.mark.parametrize("slices", [15])
# @pytest.mark.parametrize("projection_angle_range", [(0, np.pi)])


@pytest.mark.parametrize("padding_detx", [0, 10, 50, 100])
@pytest.mark.parametrize("projections", [1500, 1801, 2560])
@pytest.mark.parametrize("detX_size", [2560])
@pytest.mark.parametrize("slices", [3, 4, 5, 10, 15, 20])
@pytest.mark.parametrize("projection_angle_range", [(0, np.pi)])

# @pytest.mark.parametrize("projections", [1500, 1801, 2560])
# @pytest.mark.parametrize("detX_size", [2560])
# @pytest.mark.parametrize("slices", [3, 4, 5, 10])
# @pytest.mark.parametrize("projection_angle_range", [(0, np.pi)])
def test_recon_LPRec3d_tomobar_0_pi_memoryhook(
slices, detX_size, projections, projection_angle_range, ensure_clean_memory
slices,
detX_size,
projections,
projection_angle_range,
padding_detx,
ensure_clean_memory,
):
__test_recon_LPRec3d_tomobar_memoryhook_common(
slices, detX_size, projections, projection_angle_range, ensure_clean_memory
slices,
detX_size,
projections,
projection_angle_range,
padding_detx,
ensure_clean_memory,
)


@pytest.mark.full
@pytest.mark.cupy
@pytest.mark.parametrize("padding_detx", [0, 10, 50, 100])
@pytest.mark.parametrize("projections", [1500, 1801, 2560, 3601])
@pytest.mark.parametrize("detX_size", [2560])
@pytest.mark.parametrize("slices", [3, 4, 5, 10, 15, 20])
@pytest.mark.parametrize("projection_angle_range", [(0, np.pi)])
def test_recon_LPRec3d_tomobar_0_pi_memoryhook_full(
slices, detX_size, projections, projection_angle_range, ensure_clean_memory
slices,
detX_size,
projections,
projection_angle_range,
padding_detx,
ensure_clean_memory,
):
__test_recon_LPRec3d_tomobar_memoryhook_common(
slices, detX_size, projections, projection_angle_range, ensure_clean_memory
slices,
detX_size,
projections,
projection_angle_range,
padding_detx,
ensure_clean_memory,
)


@pytest.mark.full
@pytest.mark.cupy
@pytest.mark.parametrize("padding_detx", [0, 10, 50, 100])
@pytest.mark.parametrize("projections", [1500, 1801, 2560, 3601])
@pytest.mark.parametrize("detX_size", [2560])
@pytest.mark.parametrize("slices", [3, 4, 5, 10, 15, 20])
@pytest.mark.parametrize(
"projection_angle_range", [(0, np.pi), (0, 2 * np.pi), (-np.pi / 2, np.pi / 2)]
)
def test_recon_LPRec3d_tomobar_memoryhook_full(
slices, detX_size, projections, projection_angle_range, ensure_clean_memory
slices,
detX_size,
projections,
projection_angle_range,
padding_detx,
ensure_clean_memory,
):
__test_recon_LPRec3d_tomobar_memoryhook_common(
slices, detX_size, projections, projection_angle_range, ensure_clean_memory
slices,
detX_size,
projections,
projection_angle_range,
padding_detx,
ensure_clean_memory,
)


def __test_recon_LPRec3d_tomobar_memoryhook_common(
slices, detX_size, projections, projection_angle_range, ensure_clean_memory
slices,
detX_size,
projections,
projection_angle_range,
padding_detx,
ensure_clean_memory,
):
angles_number = projections
data = cp.random.random_sample((angles_number, slices, detX_size), dtype=np.float32)
Expand All @@ -642,6 +676,7 @@ def __test_recon_LPRec3d_tomobar_memoryhook_common(
projection_angle_range[0], projection_angle_range[1], data.shape[0]
)
kwargs["center"] = 1280
kwargs["detector_pad"] = padding_detx
kwargs["recon_size"] = detX_size
kwargs["recon_mask_radius"] = 0.8

Expand Down Expand Up @@ -687,9 +722,9 @@ def __test_recon_LPRec3d_tomobar_memoryhook_common(
if slices <= 3:
assert percents_relative_maxmem <= 75
elif slices <= 5:
assert percents_relative_maxmem <= 60
assert percents_relative_maxmem <= 63
else:
assert percents_relative_maxmem <= 47
assert percents_relative_maxmem <= 50


@pytest.mark.cupy
Expand Down
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