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| author | Andreas Nevalainen <andreas.nevalainen@arm.com> | 2020-11-17 09:16:11 +0100 |
|---|---|---|
| committer | patrik.gustavsson <patrik.gustavsson@arm.com> | 2020-11-18 11:14:20 +0000 |
| commit | ed67b88e4b0ce21c42dabe5b2a199afd8e95b17f (patch) | |
| tree | 459e051892d3e0e9bb017453fa051c963ec2c06f | |
| parent | b0ca274e904ca9080f2baa22fdb538c58b20aab2 (diff) | |
| download | ethos-u-vela-ed67b88e4b0ce21c42dabe5b2a199afd8e95b17f.tar.gz | |
MLMBED-3468: Update scale tensors SRAM size calculation
Updated SRAM size calculation for scale tensors.
Change-Id: Idaecc3bf0c83d58ea70163bfd194c594295b66db
Signed-off-by: Andreas Nevalainen <andreas.nevalainen@arm.com>
| -rw-r--r-- | ethosu/vela/scheduler.py | 49 |
1 files changed, 26 insertions, 23 deletions
diff --git a/ethosu/vela/scheduler.py b/ethosu/vela/scheduler.py index 526cc0e..4af83a1 100644 --- a/ethosu/vela/scheduler.py +++ b/ethosu/vela/scheduler.py @@ -1030,7 +1030,7 @@ class DynamicProgrammingScheduler: for cp in sg.cascaded_passes: if cp.strategy == SchedulingStrategy.IfmStream: for ps in cp.passes: - if ps.scale_tensor and (cp.sram_used + ps.scale_tensor.storage_size()) <= self.sram_limit: + if ps.scale_tensor: tens = ps.scale_tensor # Find op using scale tensor @@ -1041,28 +1041,31 @@ class DynamicProgrammingScheduler: new_tens = tens.clone_into_fast_storage(arch) new_tens.consumer_list = tens.consumer_list.copy() new_tens.purpose = TensorPurpose.FSBias - - # Create DMA cmd - dma_cmd = Operation(Op.DMA, tens.ops[0].name + "_dma") - dma_cmd.inputs = [tens] - dma_cmd.set_output_tensor(new_tens) - dma_cmd.attrs["source"] = tens.mem_area - dma_cmd.attrs["destination"] = new_tens.mem_area - dma_cmd.run_on_npu = True - - tens.consumer_list.clear() - tens.consumer_list.append(dma_cmd) - - # Replace tensor and op - idx = op.inputs.index(tens) - op.inputs[idx] = new_tens - - ps.ops.insert(0, dma_cmd) - ps.scale_tensor = new_tens - ps.intermediates.append(new_tens) - ps.cascade.intermediates.append(new_tens) - - cp.sram_used += tens.storage_size() + new_tens.element_size_bytes = 10 + new_tens_size = new_tens.storage_size() + + if (cp.sram_used + new_tens_size) <= self.sram_limit: + # Create DMA cmd + dma_cmd = Operation(Op.DMA, tens.ops[0].name + "_dma") + dma_cmd.inputs = [tens] + dma_cmd.set_output_tensor(new_tens) + dma_cmd.attrs["source"] = tens.mem_area + dma_cmd.attrs["destination"] = new_tens.mem_area + dma_cmd.run_on_npu = True + + tens.consumer_list.clear() + tens.consumer_list.append(dma_cmd) + + # Replace tensor and op + idx = op.inputs.index(tens) + op.inputs[idx] = new_tens + + ps.ops.insert(0, dma_cmd) + ps.scale_tensor = new_tens + ps.intermediates.append(new_tens) + ps.cascade.intermediates.append(new_tens) + + cp.sram_used += new_tens_size def schedule_passes(nng, arch, options: SchedulerOptions): |