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Merged
merged 5 commits into from
Apr 22, 2022
Merged

replace m_new with m_new0, wherever reasonable #521

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2356c46
replace m_new with m_new0, wherever reasonable
v923z Apr 18, 2022
341e1bb
remove MICROPY_GC_CONSERVATIVE_CLEAR guards
v923z Apr 22, 2022
6b4cae6
remove dangling memory fragments created by m_new0
v923z Apr 22, 2022
36a13d9
fix tests
v923z Apr 22, 2022
a3dce3b
fix delete error
v923z Apr 22, 2022
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remove MICROPY_GC_CONSERVATIVE_CLEAR guards
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@v923z
v923z committed Apr 22, 2022
commit 341e1bbb6a04a4939e60d67f860a0efec28b66c3
26 changes: 3 additions & 23 deletions code/ndarray.c
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Original file line number Diff line number Diff line change
Expand Up @@ -164,9 +164,6 @@ void ndarray_fill_array_iterable(mp_float_t *array, mp_obj_t iterable) {
#if ULAB_HAS_FUNCTION_ITERATOR
size_t *ndarray_new_coords(uint8_t ndim) {
size_t *coords = m_new0(size_t, ndim);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(coords, 0, ndim*sizeof(size_t));
#endif
return coords;
}

Expand Down Expand Up @@ -623,9 +620,6 @@ ndarray_obj_t *ndarray_new_ndarray(uint8_t ndim, size_t *shape, int32_t *strides
uint8_t *array = m_new0(byte, len);
// this should set all elements to 0, irrespective of the of the dtype (all bits are zero)
// we could, perhaps, leave this step out, and initialise the array only, when needed
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(array, 0, len);
#endif
ndarray->array = array;
ndarray->origin = array;
return ndarray;
Expand Down Expand Up @@ -1064,10 +1058,6 @@ bool ndarray_can_broadcast(ndarray_obj_t *lhs, ndarray_obj_t *rhs, uint8_t *ndim
//
// 1. the two shapes are either equal
// 2. one of the shapes is 1
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(lstrides, 0, sizeof(size_t)*ULAB_MAX_DIMS);
memset(rstrides, 0, sizeof(size_t)*ULAB_MAX_DIMS);
#endif

lstrides[ULAB_MAX_DIMS - 1] = lhs->strides[ULAB_MAX_DIMS - 1];
rstrides[ULAB_MAX_DIMS - 1] = rhs->strides[ULAB_MAX_DIMS - 1];
Expand Down Expand Up @@ -1101,9 +1091,6 @@ bool ndarray_can_broadcast_inplace(ndarray_obj_t *lhs, ndarray_obj_t *rhs, int32
//
// 1. the two shapes are either equal
// 2. the shapes on the right hand side is 1
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(rstrides, 0, sizeof(size_t)*ULAB_MAX_DIMS);
#endif

rstrides[ULAB_MAX_DIMS - 1] = rhs->strides[ULAB_MAX_DIMS - 1];
for(uint8_t i=ULAB_MAX_DIMS; i > 0; i--) {
Expand Down Expand Up @@ -1154,10 +1141,6 @@ static mp_bound_slice_t generate_slice(mp_int_t n, mp_obj_t index) {
static ndarray_obj_t *ndarray_view_from_slices(ndarray_obj_t *ndarray, mp_obj_tuple_t *tuple) {
size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *strides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
memset(strides, 0, sizeof(size_t)*ULAB_MAX_DIMS);
#endif

uint8_t ndim = ndarray->ndim;

Expand Down Expand Up @@ -1199,9 +1182,9 @@ void ndarray_assign_view(ndarray_obj_t *view, ndarray_obj_t *values) {
return;
}
uint8_t ndim = 0;
size_t *shape = m_new(size_t, ULAB_MAX_DIMS);
int32_t *lstrides = m_new(int32_t, ULAB_MAX_DIMS);
int32_t *rstrides = m_new(int32_t, ULAB_MAX_DIMS);
size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *lstrides = m_new0(int32_t, ULAB_MAX_DIMS);
int32_t *rstrides = m_new0(int32_t, ULAB_MAX_DIMS);
if(!ndarray_can_broadcast(view, values, &ndim, shape, lstrides, rstrides)) {
mp_raise_ValueError(translate("operands could not be broadcast together"));
m_del(size_t, shape, ULAB_MAX_DIMS);
Expand Down Expand Up @@ -2170,9 +2153,6 @@ mp_obj_t ndarray_reshape_core(mp_obj_t oin, mp_obj_t _shape, bool inplace) {
mp_raise_ValueError(translate("maximum number of dimensions is 4"));
}
size_t *new_shape = m_new0(size_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(new_shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
#endif

size_t new_length = 1;
for(uint8_t i=0; i < shape->len; i++) {
Expand Down
6 changes: 0 additions & 6 deletions code/numpy/create.c
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Original file line number Diff line number Diff line change
Expand Up @@ -36,9 +36,6 @@ static mp_obj_t create_zeros_ones_full(mp_obj_t oshape, uint8_t dtype, mp_obj_t
mp_raise_TypeError(translate("too many dimensions"));
}
size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, ULAB_MAX_DIMS * sizeof(size_t));
#endif

size_t i = 0;
mp_obj_iter_buf_t iter_buf;
Expand Down Expand Up @@ -249,9 +246,6 @@ mp_obj_t create_concatenate(size_t n_args, const mp_obj_t *pos_args, mp_map_t *k
}
int8_t axis = (int8_t)args[1].u_int;
size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
#endif
mp_obj_tuple_t *ndarrays = MP_OBJ_TO_PTR(args[0].u_obj);

// first check, whether the arrays are compatible
Expand Down
6 changes: 0 additions & 6 deletions code/numpy/io/io.c
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Expand Up @@ -132,9 +132,6 @@ static mp_obj_t io_load(mp_obj_t file) {
io_read_(stream, stream_p, buffer, "', 'fortran_order': False, 'shape': (", 37, &error);

size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t) * ULAB_MAX_DIMS);
#endif

uint16_t bytes_to_read = MIN(ULAB_IO_BUFFER_SIZE, header_length - 51);
// bytes_to_read is 128 at most. This should be enough to contain a
Expand Down Expand Up @@ -389,9 +386,6 @@ static mp_obj_t io_loadtxt(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw
}

size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t) * ULAB_MAX_DIMS);
#endif

#if ULAB_MAX_DIMS == 1
shape[0] = rows;
Expand Down
4 changes: 0 additions & 4 deletions code/numpy/linalg/linalg_tools.c
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Expand Up @@ -28,10 +28,6 @@ bool linalg_invert_matrix(mp_float_t *data, size_t N) {
// will be returned after all the transformations
mp_float_t *unit = m_new0(mp_float_t, N*N);
mp_float_t elem = 1.0;
// initialise the unit matrix
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(unit, 0, sizeof(mp_float_t)*N*N);
#endif

for(size_t m=0; m < N; m++) {
memcpy(&unit[m * (N+1)], &elem, sizeof(mp_float_t));
Expand Down
27 changes: 0 additions & 27 deletions code/numpy/numerical.c
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Expand Up @@ -517,10 +517,6 @@ static mp_obj_t numerical_argmin_argmax_ndarray(ndarray_obj_t *ndarray, mp_obj_t
uint8_t *array = (uint8_t *)ndarray->array;
size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *strides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(strides, 0, sizeof(uint32_t)*ULAB_MAX_DIMS);
memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
#endif

numerical_reduce_axes(ndarray, ax, shape, strides);
uint8_t index = ULAB_MAX_DIMS - ndarray->ndim + ax;
Expand Down Expand Up @@ -641,10 +637,6 @@ static mp_obj_t numerical_sort_helper(mp_obj_t oin, mp_obj_t axis, uint8_t inpla

size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *strides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
memset(strides, 0, sizeof(uint32_t)*ULAB_MAX_DIMS);
#endif

numerical_reduce_axes(ndarray, ax, shape, strides);
ax = ULAB_MAX_DIMS - ndarray->ndim + ax;
Expand Down Expand Up @@ -741,10 +733,6 @@ mp_obj_t numerical_argsort(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw

size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *strides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
memset(strides, 0, sizeof(uint32_t)*ULAB_MAX_DIMS);
#endif
numerical_reduce_axes(ndarray, ax, shape, strides);

// We could return an NDARRAY_UINT8 array, if all lengths are shorter than 256
Expand Down Expand Up @@ -956,9 +944,6 @@ mp_obj_t numerical_diff(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_ar

memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
int32_t *strides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(strides, 0, sizeof(int32_t)*ULAB_MAX_DIMS);
#endif
numerical_reduce_axes(ndarray, ax, shape, strides);

if(ndarray->dtype == NDARRAY_UINT8) {
Expand Down Expand Up @@ -1094,10 +1079,6 @@ mp_obj_t numerical_median(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_

size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *strides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
memset(strides, 0, sizeof(uint32_t)*ULAB_MAX_DIMS);
#endif
numerical_reduce_axes(ndarray, ax, shape, strides);

ax = ULAB_MAX_DIMS - ndarray->ndim + ax;
Expand Down Expand Up @@ -1251,18 +1232,10 @@ mp_obj_t numerical_roll(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_ar

size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *strides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
memset(strides, 0, sizeof(int32_t)*ULAB_MAX_DIMS);
#endif
numerical_reduce_axes(ndarray, ax, shape, strides);

size_t *rshape = m_new0(size_t, ULAB_MAX_DIMS);
int32_t *rstrides = m_new0(int32_t, ULAB_MAX_DIMS);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(rshape, 0, sizeof(size_t)*ULAB_MAX_DIMS);
memset(rstrides, 0, sizeof(int32_t)*ULAB_MAX_DIMS);
#endif
numerical_reduce_axes(results, ax, rshape, rstrides);

ax = ULAB_MAX_DIMS - ndarray->ndim + ax;
Expand Down
6 changes: 0 additions & 6 deletions code/numpy/transform.c
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Expand Up @@ -84,9 +84,6 @@ static mp_obj_t transform_compress(size_t n_args, const mp_obj_t *pos_args, mp_m

if(axis == mp_const_none) {
result = ndarray_new_linear_array(true_count, ndarray->dtype);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(rstrides, 0, ndarray->ndim * sizeof(int32_t));
#endif

rstrides[ULAB_MAX_DIMS - 1] = ndarray->itemsize;
rshape[ULAB_MAX_DIMS - 1] = 0;
Expand Down Expand Up @@ -254,9 +251,6 @@ static mp_obj_t transform_delete(size_t n_args, const mp_obj_t *pos_args, mp_map

if(axis == mp_const_none) {
result = ndarray_new_linear_array(ndarray->len - index_len, ndarray->dtype);
#if !MICROPY_GC_CONSERVATIVE_CLEAR
memset(rstrides, 0, ndarray->ndim * sizeof(int32_t));
#endif
rstrides[ULAB_MAX_DIMS - 1] = ndarray->itemsize;
memset(rshape, 0, sizeof(size_t) * ULAB_MAX_DIMS);
// rshape[ULAB_MAX_DIMS - 1] = 0;
Expand Down