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| author | Fredrik Svedberg <fredrik.svedberg@arm.com> | 2020-09-04 09:46:17 +0200 |
|---|---|---|
| committer | patrik.gustavsson <patrik.gustavsson@arm.com> | 2020-09-07 06:23:54 +0000 |
| commit | 835d8e10f33f411664cebe65d3f6a872f6cc849a (patch) | |
| tree | 60c0cfd477cac7b604ade275ec82f54cbb14e9e8 /ethosu/vela/softmax.py | |
| parent | e5cf95b8c3de4e1e4cbc7046cafd4d84c7492596 (diff) | |
| download | ethos-u-vela-835d8e10f33f411664cebe65d3f6a872f6cc849a.tar.gz | |
[MLBEDSW-2928] Add batching to softmax
Added batching to softmax by reshaping the input.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: I0b516f9bf2410fb86372b229beba4a7280c498cc
Diffstat (limited to 'ethosu/vela/softmax.py')
| -rw-r--r-- | ethosu/vela/softmax.py | 14 |
1 files changed, 9 insertions, 5 deletions
diff --git a/ethosu/vela/softmax.py b/ethosu/vela/softmax.py index 2834f8c2..9e8b846d 100644 --- a/ethosu/vela/softmax.py +++ b/ethosu/vela/softmax.py @@ -201,6 +201,14 @@ class SoftMax: ifm = self.op.inputs[0] ofm = self.op.outputs[0] + # Reshape ifm/ofm (if needed) + full_shape = ifm.get_full_shape() + if full_shape[0] > 1: + full_shape[1] *= full_shape[0] + full_shape[0] = 1 + ifm = create_reshape_tensor(ifm, full_shape) + ofm = create_reshape_tensor(ofm, full_shape, False) + if ifm.dtype in (DataType.uint8, DataType.int8) and ofm.dtype == ifm.dtype: return self.get_graph_8bit(ifm, ofm) elif ifm.dtype == DataType.int16 and ofm.dtype == DataType.int16: @@ -211,8 +219,6 @@ class SoftMax: def get_graph_8bit(self, ifm, ofm): exp_lut = self.generate_exp_table(self.op.attrs.get("beta", 1.0), ifm.quantization.scale_f32) - ifm = create_reshape_tensor(ifm, ifm.get_full_shape()) - ofm = create_reshape_tensor(ofm, ofm.get_full_shape(), False) no_scale_quant = ifm.quantization.clone() no_scale_quant.scale_f32 = None no_scale_quant.zero_point = 0 @@ -242,7 +248,7 @@ class SoftMax: # PASS 1 - Sub+LUT(exp) sub_op = Operation("SubAct", self.op.name + "_sub1") sub_op.add_input_tensor(ifm) - sub_op.add_input_tensor(ifm_max) + sub_op.add_input_tensor(create_reshape_tensor(ifm_max, [1, ifm.shape[1], ifm.shape[2], 1])) sub_op.set_activation_lut( create_const_tensor( sub_op.name + "_lut", [1, 1, 1, 256], DataType.int32, exp_lut, np.int32, TensorPurpose.LUT @@ -463,8 +469,6 @@ class SoftMax: return shr30_op def get_graph_int16(self, ifm, ofm): - ifm = create_reshape_tensor(ifm, ifm.get_full_shape()) - ofm = create_reshape_tensor(ofm, ofm.get_full_shape(), False) no_scale_quant = ifm.quantization.clone() no_scale_quant.scale_f32 = None |