[ETHOSU][MicroNPU][Pass] Add a pass to replicate pads #14909
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cc @neildhickey, @ekalda, @ilyag-grovety, @Aleksei-grovety @arina-grovety |
ekalda
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May 30, 2023
sergio-grovety
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@tvm-bot rerun |
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| if op_pairs[0] == "depthwise": | ||
| weight_shape = [kernel_shape[0], kernel_shape[1], ifm_shape[3], 1] | ||
| weight = tf.constant(np.random.uniform(size=weight_shape), dtype=tf.float32) | ||
| x1 = tf.nn.depthwise_conv2d( | ||
| x, weight, strides=tf_strides, padding=op_padding, dilations=dilation | ||
| ) | ||
| else: | ||
| weight_shape = [kernel_shape[0], kernel_shape[1], ifm_shape[3], 3] | ||
| weight = tf.constant(np.random.uniform(size=weight_shape), dtype=tf.float32) | ||
| x1 = tf.nn.conv2d( | ||
| x, | ||
| weight, | ||
| strides=tf_strides, | ||
| padding=op_padding, | ||
| dilations=dilation, | ||
| ) |
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Here the same code as on lines 3706 - 3721, it can be put into a separate function.
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. | ||
| "Adds pads so that each conv2d operator has only one consumer" |
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Maybe "Adds pads to each conv2d operator so that each pad has only one consumer."?
| new_conv2d_args = [] | ||
| for i, arg in enumerate(call.args): | ||
| if i == 0: | ||
| new_conv2d_args.append(self.visit(new_pad)) |
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new_pad is visited twice the first time on line 59.
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@tvm-bot rerun |
ekalda
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Jun 19, 2023
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Thanks @sergio-grovety, great work! Bar @Aleksei-grovety suggestions, I only had one nit and two more general points:
- This pass is necessary due to how we do pattern matching for Ethos-U and is therefore coupled to Ethos-U integration, so I don't think it makes much sense to have it among generic Relay transformation passes. Maybe move it to somewhere into
ethosunamespace, e.g. into codegen. - Testing - while legalization test is the most important test for this kind of change, I think it would also be good to have a simple lightweight codegen test for this kind of graph topology. Since the pass creates a new conv2d, there is some risk of constants getting messed up, but a simple codegen test should eliminate that risk.
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| def __init__(self): | ||
| ExprMutator.__init__(self) | ||
| self.hashes = set() |
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Nit: Maybe add a comment what self.hashes represents
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ekalda
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| @pytest.mark.parametrize("accel_type", ACCEL_TYPES) | ||
| @pytest.mark.parametrize("ifm_shape", [(1, 55, 32, 3)]) | ||
| @pytest.mark.parametrize( | ||
| "kernel_shape, activation_function", | ||
| [((3, 3), "RELU"), ((1, 2), "NONE")], | ||
| ) | ||
| @pytest.mark.parametrize("strides, dilation", [((3, 2), (1, 1))]) | ||
| @pytest.mark.parametrize("op_padding", ["SAME", "VALID"]) | ||
| @pytest.mark.parametrize("sep_padding", [(0, 0, 1, 1), (7, 5, 4, 5)]) | ||
| @pytest.mark.parametrize( | ||
| "op_pairs", [("conv2d", "conv2d"), ("depthwise", "depthwise"), ("conv2d", "depthwise")] | ||
| ) |
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This is 128 codegen tests, which would noticeably increase CI time. I think the variations on kernel_shape, activation_function, op_padding and sep_padding are exercised by other tests as well, so these values could be kept constant. Also, if we are parametrizing over one value, it doesn't need to be expressed with parametrize and can be included into the test code.
ekalda
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Jul 13, 2023
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LGTM! Thanks @sergio-grovety, @Aleksei-grovety and @arina-grovety!
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Thanks all, this is merged now! |
junrushao
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Jul 24, 2023
Added a pass to to handle the situation when nn.pad operator has more than one qnn.conv2d consumer.
pad
/ \
Conv2D Conv2D
In this case, because of the peculiarities of pattern parsing, conv2d does not get into the composite for the NPU. Therefore, pads are added so that each has only one consumer.
---------
Co-authored-by: Sergey Smirnov <89378719+sergey-grovety@users.noreply.github.com>
Co-authored-by: Arina <117634809+arina-grovety@users.noreply.github.com>
Co-authored-by: arina.naumova <naumova@grovety.com>
junrushao
pushed a commit
to junrushao/tvm
that referenced
this pull request
Jul 27, 2023
Added a pass to to handle the situation when nn.pad operator has more than one qnn.conv2d consumer.
pad
/ \
Conv2D Conv2D
In this case, because of the peculiarities of pattern parsing, conv2d does not get into the composite for the NPU. Therefore, pads are added so that each has only one consumer.
---------
Co-authored-by: Sergey Smirnov <89378719+sergey-grovety@users.noreply.github.com>
Co-authored-by: Arina <117634809+arina-grovety@users.noreply.github.com>
Co-authored-by: arina.naumova <naumova@grovety.com>
junrushao
pushed a commit
to junrushao/tvm
that referenced
this pull request
Jul 30, 2023
Added a pass to to handle the situation when nn.pad operator has more than one qnn.conv2d consumer.
pad
/ \
Conv2D Conv2D
In this case, because of the peculiarities of pattern parsing, conv2d does not get into the composite for the NPU. Therefore, pads are added so that each has only one consumer.
---------
Co-authored-by: Sergey Smirnov <89378719+sergey-grovety@users.noreply.github.com>
Co-authored-by: Arina <117634809+arina-grovety@users.noreply.github.com>
Co-authored-by: arina.naumova <naumova@grovety.com>
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Added a pass to to handle the situation when nn.pad operator has more than one qnn.conv2d consumer.
In this case, because of the peculiarities of pattern parsing, conv2d does not get into the composite for the NPU. Therefore, pads are added so that each has only one consumer.