vela: Remove and change CLI options
- Removed unused --show-minimum-possible-allocation
- Change --allocation-alignment to --cpu-tensor-alignment
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I00e367c3190aeea08a3f136332711e9accc85ba3
diff --git a/ethosu/vela/tensor_allocation.py b/ethosu/vela/tensor_allocation.py
index 8329a61..d1a3372 100644
--- a/ethosu/vela/tensor_allocation.py
+++ b/ethosu/vela/tensor_allocation.py
@@ -85,7 +85,7 @@
ps.sram_used = sram_used
-def print_allocation(lrs, mem_area, mem_type_set, sg, verbose_allocation, show_minimum_possible_allocation):
+def print_allocation(lrs, mem_area, mem_type_set, sg, verbose_allocation):
if verbose_allocation:
if mem_type_set == set((MemType.Permanent_NPU,)) or mem_type_set == set((MemType.Permanent_CPU,)):
print("allocation for", mem_area, "- constant tensors in", sg.placement.name, "subgraph(s)")
@@ -108,13 +108,6 @@
print("Memory usage: {} ({:#x}) bytes / {:.1f} KB".format(mem_usage, mem_usage, mem_usage / 1024))
print()
- if show_minimum_possible_allocation and mem_area == MemArea.Sram:
- min_possible_allocation = max(cps.sram_used for cps in sg.cascaded_passes)
- print(
- "Min possible allocation %d bytes / %.1f KB / %.1f MB"
- % (min_possible_allocation, min_possible_allocation / 1024, min_possible_allocation / 1024 / 1024)
- )
-
def allocate_tensors(
nng,
@@ -124,9 +117,8 @@
mem_type_set,
tensor_allocator=TensorAllocator.Greedy,
verbose_allocation=False,
- show_minimum_possible_allocation=False,
lr_graph=None,
- allocation_alignment=Tensor.AllocationQuantum,
+ cpu_tensor_alignment=Tensor.AllocationQuantum,
max_size=None,
dry_test=False,
):
@@ -138,15 +130,15 @@
mem_type_set,
ignore_subgraph_input_output_tensors=ignore_subgraph_input_output_tensors,
lr_graph=lr_graph,
- allocation_alignment=allocation_alignment,
+ cpu_tensor_alignment=cpu_tensor_alignment,
)
if lrs.ranges:
tens_alloc = tensor_allocator
if tens_alloc == TensorAllocator.Greedy:
- total_sz = greedy_allocate_live_ranges(sg, arch, lrs, mem_area, allocation_alignment, verbose_allocation)
+ total_sz = greedy_allocate_live_ranges(sg, arch, lrs, mem_area, cpu_tensor_alignment, verbose_allocation)
elif tens_alloc == TensorAllocator.LinearAlloc:
- total_sz = linear_allocate_live_ranges(lrs, allocation_alignment)
+ total_sz = linear_allocate_live_ranges(lrs, cpu_tensor_alignment)
else:
assert 0
alloc_ok = max_size is None or total_sz <= max_size
@@ -171,7 +163,7 @@
nng.total_size[mem_area] = nng.total_size.get(mem_area, 0) + sum(tens.storage_size() for tens in lrs.ranges)
nng.total_elements[mem_area] = nng.total_elements.get(mem_area, 0) + sum(tens.elements() for tens in lrs.ranges)
- print_allocation(lrs, mem_area, mem_type_set, sg, verbose_allocation, show_minimum_possible_allocation)
+ print_allocation(lrs, mem_area, mem_type_set, sg, verbose_allocation)
if mem_area == MemArea.Sram:
# Mark Sram usage for all subgraphs