コード例 #1
0
ファイル: convert_r_to_rgba.py プロジェクト: unixnme/webdnn
def convert_r_to_rgba(op: ConvertRtoRGBA) -> List[Kernel]:
    x = op.inputs["x0"]
    y = op.outputs["y"]

    assert ChannelMode.get(x) == ChannelModeEnum.R
    assert ChannelMode.get(y) == ChannelModeEnum.RGBA

    orders, shape_dicts = simplify_orders([x, y])
    shapes = {v: [shape_dicts[v][a] for a in orders[v].axes] for v in [x, y]}
    strides = {
        v:
        [mul(shapes[v][orders[v].axes_dict[a] + 1:]) for a in orders[v].axes]
        for v in [x, y]
    }
    stride_dicts = {v: AxisKeyDict(orders[v].axes, strides[v]) for v in [x, y]}

    # Change x's shapes and strides order to same as y's order
    shapes[x] = [
        shape_dicts[x][a] if a in orders[x].axes else 1 for a in orders[y].axes
    ]
    strides[x] = [
        stride_dicts[x][a] if a in orders[x].axes else 1
        for a in orders[y].axes
    ]

    # Padding shapes and strides to 4D
    if orders[y].ndim > 4:
        raise NotImplementedError(f"Too large number of dimension: {y}")

    for v in [x, y]:
        shape = shapes[v]
        stride = strides[v]
        while len(shape) < 4:
            stride.append(1)
            shape.append(1)

    name_injector = KernelNameInjector(op)
    uniform_injector = UniformInjector()
    uniform_injector.register({
        "sampler_x": x,
        "texture_stride_y": texture_stride(y),
        "variable_shape_y": shapes[y],
        "variable_stride_y": strides[y],
        "texture_shape_x": texture_shape(x),
        "texture_stride_x": texture_stride(x),
        "variable_shape_x": shapes[x],
        "variable_stride_x": strides[x],
    })
    source = template
    source = uniform_injector.inject(source)
    source = name_injector.inject(source)
    kernel = Kernel(source, name_injector.name, uniform_injector.samplers,
                    uniform_injector.uniforms, y)

    return [kernel]
コード例 #2
0
ファイル: split_axis.py プロジェクト: zhangaz1/webdnn
def split_axis(op: SplitAxis) -> List[Kernel]:
    x = op.inputs["x"]
    ys = [op.outputs[f"y{i}"] for i in range(len(op.outputs))]
    sections = [0] + op.sections
    axis = op.axis

    kernels = []

    for i, y in enumerate(ys):
        assert x.order.check_same_axes(y.order)
        assert ChannelMode.get(x) == ChannelMode.get(y) == ChannelModeEnum.R

        if x.ndim > 4:
            # simplify orders
            orders, shape_dicts = simplify_orders([x, y], keep_axes=[axis])
            shapes = {
                v: [shape_dicts[v][a] for a in order.axes]
                for v, order in orders.items()
            }
            strides = {
                v: [mul(shapes[v][i + 1:]) for i in range(order.ndim)]
                for v, order in orders.items()
            }
        else:
            orders = {y: y.order, x: x.order}
            shapes = {y: y.shape, x: x.shape}
            strides = {y: y.stride, x: x.stride}

        code = KernelCode([
            f"""
void main() {{
    """,
            Type.Ivec.get_name(shapes[x]), f""" variable_position_x = """,
            change_order(
                convert_position("gl_FragCoord.yx",
                                 texture_shape(y)[:2],
                                 texture_stride(y)[:2], shapes[y], strides[y]),
                orders[y], orders[x]), f""";
    variable_position_x[{orders[x].axes_dict[axis]}] += {sections[i]};

    gl_FragColor.r = texture2D(""", x, ",",
            convert_coord("variable_position_x", shapes[x], strides[x],
                          texture_shape(x)[:2][::-1],
                          texture_stride(x)[:2][::-1]), f""").r;
}}
"""
        ],
                          name=op.__class__.__name__)
        source = code.generate()
        kernels.append(
            Kernel(source, code.name, code.samplers, code.uniforms, y))

    return kernels
コード例 #3
0
def concat(op: Concat) -> List[Kernel]:
    assert len(op.inputs) == 2
    x0 = op.inputs["x0"]
    x1 = op.inputs["x1"]
    y = op.outputs["y"]
    axis = op.axis

    assert x0.order.check_same_axes(y.order)
    assert x1.order.check_same_axes(y.order)
    assert ChannelMode.get(x0) == ChannelMode.get(x1) == ChannelMode.get(y)

    if x0.ndim > 4 or x1.ndim > 4:
        # simplify orders
        orders, shape_dicts = simplify_orders([x0, x1, y], keep_axes=[axis])
        shapes = {v: [shape_dicts[v][a] for a in order.axes] for v, order in orders.items()}
        strides = {v: [mul(shapes[v][i + 1:]) for i in range(order.ndim)] for v, order in orders.items()}

    else:
        orders = {y: y.order, x0: x0.order, x1: x1.order}
        shape_dicts = {y: y.shape_dict, x0: x0.shape_dict, x1: x1.shape_dict}
        shapes = {y: y.shape, x0: x0.shape, x1: x1.shape}
        strides = {y: y.stride, x0: x0.stride, x1: x1.stride}

    code = KernelCode([f"""
void main() {{
""", Type.Ivec.get_name(shapes[x0]), f""" variable_position_x0 = """, change_order(
        convert_position("gl_FragCoord.yx", texture_shape(y)[:2], texture_stride(y)[:2], shapes[y], strides[y]),
        orders[y], orders[x0]
    ), f""";
""", Type.Ivec.get_name(shapes[x1]), f""" variable_position_x1 = """, change_order(
        convert_position("gl_FragCoord.yx", texture_shape(y)[:2], texture_stride(y)[:2], shapes[y], strides[y]),
        orders[y], orders[x1]
    ), f""";
    variable_position_x1[{orders[x1].axes_dict[axis]}] -= {x0.shape_dict[axis]};

    gl_FragColor.r = (
        (variable_position_x0[{orders[x0].axes_dict[axis]}] >= {shape_dicts[x0][axis]})
        ? texture2D(""", x1, ",", convert_coord("variable_position_x1", shapes[x1], strides[x1], texture_shape(x1)[:2][::-1],
                                                texture_stride(x1)[:2][::-1]), f""")
        : texture2D(""", x0, ",", convert_coord("variable_position_x0", shapes[x0], strides[x0], texture_shape(x0)[:2][::-1],
                                                texture_stride(x0)[:2][::-1]), f""")
    ).r;
}}
"""], name=op.__class__.__name__)
    source = code.generate()
    return [Kernel(
        source,
        code.name,
        code.samplers,
        code.uniforms,
        y
    )]
コード例 #4
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def reduce_kernel(op: Reduce):
    x = op.inputs["x"]
    y = op.outputs["y"]
    axis = op.axis

    orders, shape_dicts = simplify_orders([x, y], keep_axes=[axis])

    # Padding shapes and strides to 4D
    if orders[y].ndim > 4:
        raise NotImplementedError(f"Too large number of dimension: {y}")

    shapes = {v: [shape_dicts[v][a] for a in orders[v].axes] for v in [x, y]}
    strides = {
        v:
        [mul(shapes[v][orders[v].axes_dict[a] + 1:]) for a in orders[v].axes]
        for v in [x, y]
    }
    stride_dicts = {v: AxisKeyDict(orders[v].axes, strides[v]) for v in [x, y]}

    # Change x's shapes and strides order to same as y's order
    x_virtual_shape = [
        shape_dicts[x][a] if a in orders[x].axes else 1 for a in orders[y].axes
    ]
    x_virtual_stride = [
        stride_dicts[x][a] if a in orders[x].axes else 1
        for a in orders[y].axes
    ]
    while len(x_virtual_shape) < 3:
        x_virtual_stride.append(1)
        x_virtual_shape.append(stride_dicts[x][axis])
    x_virtual_shape.append(shape_dicts[x][axis])
    x_virtual_stride.append(stride_dicts[x][axis])

    y_virtual_shape = shapes[y]
    y_virtual_stride = strides[y]
    while len(y_virtual_shape) < 4:
        y_virtual_stride.append(1)
        y_virtual_shape.append(1)

    code = _generate_template(op,
                              reduction_size=shape_dicts[x][axis],
                              shapes={
                                  y: y_virtual_shape,
                                  x: x_virtual_shape
                              },
                              strides={
                                  y: y_virtual_stride,
                                  x: x_virtual_stride
                              })
    source = code.generate()
    return [Kernel(source, code.name, code.samplers, code.uniforms, y)]
コード例 #5
0
def concat(op: Concat) -> List[Kernel]:
    xs = [op.inputs[f"x{i}"] for i in range(len(op.inputs) - 1)]
    workspace = op.inputs["workspace"]
    y = op.outputs["y"]
    axis = op.axis

    kernels = []

    # noinspection PyUnresolvedReferences
    inv_texture_shape_y = [
        float(np.double(1.0) / np.double(v))
        for v in texture_shape(y)[:2][::-1]
    ]

    # noinspection PyUnresolvedReferences
    inv_texture_shape_workspace = [
        float(np.double(1.0) / np.double(v))
        for v in texture_shape(workspace)[:2][::-1]
    ]

    sections = [0]
    for x in xs:
        sections.append(sections[-1] + x.shape_dict[axis])

    for i, x in enumerate(xs):
        assert x.order.check_same_axes(y.order)
        assert ChannelMode.get(x) == ChannelMode.get(y)

        if x.ndim > 4:
            # simplify orders
            orders, shape_dicts = simplify_orders([x, y], keep_axes=[axis])
            shapes = {
                v: [shape_dicts[v][a] for a in order.axes]
                for v, order in orders.items()
            }
            strides = {
                v: [mul(shapes[v][i + 1:]) for i in range(order.ndim)]
                for v, order in orders.items()
            }
        else:
            orders = {y: y.order, x: x.order}
            shape_dicts = {y: y.shape_dict, x: x.shape_dict}
            shapes = {y: y.shape, x: x.shape}
            strides = {y: y.stride, x: x.stride}

        # copy xs[i] or workspace's value into y
        code1 = KernelCode([
            f"""
void main() {{
    """,
            Type.Ivec.get_name(shapes[x]), f""" variable_position_x = """,
            change_order(
                convert_position("gl_FragCoord.yx",
                                 texture_shape(y)[:2],
                                 texture_stride(y)[:2], shapes[y], strides[y]),
                orders[y], orders[x]), f""";
    variable_position_x[{orders[x].axes_dict[axis]}] -= {sections[i]};

    gl_FragColor.r = (
            variable_position_x[{orders[x].axes_dict[axis]}] < 0 || variable_position_x[{orders[x].axes_dict[axis]}] >= {shape_dicts[x][axis]}
        )
        ? texture2D(""", workspace, """, gl_FragCoord.xy * """,
            inv_texture_shape_workspace, """).r
        : texture2D(""", x, ",",
            convert_coord("variable_position_x", shapes[x], strides[x],
                          texture_shape(x)[:2][::-1],
                          texture_stride(x)[:2][::-1]), f""").r;
}}
"""
        ],
                           name="Concat_copy_to_y")

        # copy y's value into workspace
        code2 = KernelCode([
            """
void main() { gl_FragColor = texture2D(""", y, """, gl_FragCoord.xy * """,
            inv_texture_shape_y, """); }
"""
        ],
                           name="Concat_escape_to_ws")

        source1 = code1.generate()
        source2 = code2.generate()
        kernels += [
            Kernel(source1, code1.name, code1.samplers, code1.uniforms, y),
            Kernel(source2, code2.name, code2.samplers, code2.uniforms,
                   workspace)
        ]

    return kernels
コード例 #6
0
ファイル: reduce.py プロジェクト: unixnme/webdnn
def reduce_kernel(op: Reduce):
    x = op.inputs["x"]
    y = op.outputs["y"]
    axis = op.axis

    orders, shape_dicts = simplify_orders([x, y], keep_axes=[axis])

    # Padding shapes and strides to 4D
    if orders[y].ndim > 4:
        raise NotImplementedError(f"Too large number of dimension: {y}")

    shapes = {v: [shape_dicts[v][a] for a in orders[v].axes] for v in [x, y]}
    strides = {
        v:
        [mul(shapes[v][orders[v].axes_dict[a] + 1:]) for a in orders[v].axes]
        for v in [x, y]
    }
    stride_dicts = {v: AxisKeyDict(orders[v].axes, strides[v]) for v in [x, y]}

    # Change x's shapes and strides order to same as y's order
    x_virtual_shape = [
        shape_dicts[x][a] if a in orders[x].axes else 1 for a in orders[y].axes
    ]
    x_virtual_stride = [
        stride_dicts[x][a] if a in orders[x].axes else 1
        for a in orders[y].axes
    ]
    while len(x_virtual_shape) < 3:
        x_virtual_stride.append(1)
        x_virtual_shape.append(stride_dicts[x][axis])
    x_virtual_shape.append(shape_dicts[x][axis])
    x_virtual_stride.append(stride_dicts[x][axis])

    y_virtual_shape = shapes[y]
    y_virtual_stride = strides[y]
    while len(y_virtual_shape) < 4:
        y_virtual_stride.append(1)
        y_virtual_shape.append(1)

    name_injector = KernelNameInjector(op)
    uniform_injector = UniformInjector()

    uniform_injector.register({
        "texture_stride_y": texture_stride(y),
        "variable_shape_y": y_virtual_shape,
        "variable_stride_y": y_virtual_stride,
        f"sampler_x": x,
        f"texture_shape_x": texture_shape(x),
        f"texture_stride_x": texture_stride(x),
        f"variable_shape_x": x_virtual_shape,
        f"variable_stride_x": x_virtual_stride,
    })

    for name, callable in _registered_items[op.__class__].parameters.items():
        uniform_injector.register({name: callable(op)})

    # Computing logical position is required.
    source = _generate_template_convert_position(
        op, reduction_size=shape_dicts[x][axis])

    source = uniform_injector.inject(source)
    source = name_injector.inject(source)
    kernel = Kernel(source, name_injector.name, uniform_injector.samplers,
                    uniform_injector.uniforms, y)

    return [kernel]
コード例 #7
0
ファイル: elementwise.py プロジェクト: zhangaz1/webdnn
def _optimize_loop_structure(variables: List[Variable],
                             key_variable: Variable,
                             keep_axes: List[Axis] = None):
    """
    Optimize loop structure to iterate each element in variables

    Returns:
        (tuple): two elements are returned

        - First one is shape dictionary of all variables.
        - Second one is stride dictionary of all variables.
    """
    orders, shape_dicts = simplify_orders(
        variables, keep_axes=keep_axes
    )  # type: Dict[Variable, Order], Dict[Variable, AxisKeyDict[List[int]]]
    shapes = {
        v: [shape_dicts[v][a] for a in orders[v].axes]
        for v in variables
    }
    strides = {
        v:
        [mul(shapes[v][orders[v].axes_dict[a] + 1:]) for a in orders[v].axes]
        for v in variables
    }
    stride_dicts = {
        v: AxisKeyDict(orders[v].axes, strides[v])
        for v in variables
    }

    # Re-ordering shapes and strides along to key variable's order
    axes = []
    axes += [axis for axis in orders[key_variable].axes if axis not in axes]
    for v in sorted(variables, key=lambda v: orders[v].ndim):
        axes += [axis for axis in orders[v].axes if axis not in axes]

    orders = {
        v: Order(list(filter(lambda x: x in orders[v].axes, axes)))
        for v in variables
    }

    key_order = orders[key_variable]
    shapes = {
        v: [
            shape_dicts[v][a] if a in orders[v].axes else 1
            for a in key_order.axes
        ]
        for v in variables
    }
    strides = {
        v: [
            stride_dicts[v][a] if a in orders[v].axes else 1
            for a in key_order.axes
        ]
        for v in variables
    }

    # Padding shapes and strides to 4D
    if key_order.ndim > 4:
        raise NotImplementedError(f"Too large number of dimension: {v}")

    for v in variables:
        shape = shapes[v]
        stride = strides[v]
        while len(shape) < 4:
            stride.append(1)
            shape.append(1)

    return shapes, strides
コード例 #8
0
ファイル: reshape.py プロジェクト: zhangaz1/webdnn
def reshape(op: Reshape) -> List[Kernel]:
    x = op.inputs["x"]
    y = op.outputs["y"]

    in_order = op.parameters["in_order"]

    out_order = op.parameters["out_order"]

    dummy_y = Variable(y.shape, y.order).change_order(out_order)
    orders_y_dy, shapes_y_dy = simplify_orders([y, dummy_y])
    if orders_y_dy[y] == orders_y_dy[dummy_y]:
        order = Order([None] * 4)
        shape = factorize(y.size)
        stride = [mul(shape[i + 1:]) for i in range(4)]
        dummy_y = Variable(y.shape, y.order)
        shapes_y_dy = {y: shape, dummy_y: shape}
        strides_y_dy = {y: stride, dummy_y: stride}
        orders_y_dy = {y: order, dummy_y: order}

    else:
        shapes_y_dy = {v: [shapes_y_dy[v][a] for a in orders_y_dy[v].axes] for v in [y, dummy_y]}
        strides_y_dy = {v: [mul(shapes_y_dy[v][i + 1:]) for i in range(orders_y_dy[v].ndim)] for v in [y, dummy_y]}

    dummy_x = Variable(x.shape, x.order).change_order(in_order)
    orders_x_dx, shapes_x_dx = simplify_orders([x, dummy_x])
    if orders_x_dx[x] == orders_x_dx[dummy_x]:
        order = Order([None] * 4)
        shape = factorize(x.size)
        stride = [mul(shape[i + 1:]) for i in range(4)]
        dummy_x = Variable(x.shape, x.order)
        shapes_x_dx = {x: shape, dummy_x: shape}
        strides_x_dx = {x: stride, dummy_x: stride}
        orders_x_dx = {x: order, dummy_x: order}

    else:
        shapes_x_dx = {v: [shapes_x_dx[v][a] for a in orders_x_dx[v].axes] for v in [x, dummy_x]}
        strides_x_dx = {v: [mul(shapes_x_dx[v][i + 1:]) for i in range(orders_x_dx[v].ndim)] for v in [x, dummy_x]}

    # FIXME: optimize
    # y -{change_order}-> dummy_y -{convert_position}-> dummy_x -{change_order}-> x

    code = KernelCode([f"""
void main() {{
    gl_FragColor.r = texture2D(""", x, """,""", convert_coord(
        change_order(
            convert_position(
                change_order(
                    convert_position("gl_FragCoord.yx", texture_shape(y)[:2], texture_stride(y)[:2], shapes_y_dy[y], strides_y_dy[y]),
                    orders_y_dy[y], orders_y_dy[dummy_y]
                ),
                shapes_y_dy[dummy_y], strides_y_dy[dummy_y], shapes_x_dx[dummy_x], strides_x_dx[dummy_x]
            ),
            orders_x_dx[dummy_x], orders_x_dx[x]
        ),
        shapes_x_dx[x], strides_x_dx[x], texture_shape(x)[:2][::-1], texture_stride(x)[:2][::-1]
    ), f""").r;
}}
"""], name=op.__class__.__name__)
    source = code.generate()
    return [Kernel(
        source,
        code.name,
        code.samplers,
        code.uniforms,
        y
    )]