- message: url must have schema one of [http, https, file, oci]
                  rule: 'isURL(self) ? (url(self).getScheme() in ['''', ''http'',
                    ''https'', ''oci'', ''file'']) : (isURL(''http://'' + self) &&
                    url(''http://'' +self).getScheme() in ['''', ''http'', ''https'',
                    ''oci'', ''file''])'
              verificationKey:

                  rule: '!(has(self.caCertificateRefs) && size(self.caCertificateRefs)
                    > 0 && has(self.wellKnownCACertificates) && self.wellKnownCACertificates
                    != "")'
                - message: must specify either CACertificateRefs or WellKnownCACertificates
                  rule: (has(self.caCertificateRefs) && size(self.caCertificateRefs)

                - message: url must have schema one of [http, https, file, oci]
                  rule: 'isURL(self) ? (url(self).getScheme() in ['''', ''http'',
                    ''https'', ''oci'', ''file'']) : (isURL(''http://'' + self) &&
                    url(''http://'' +self).getScheme() in ['''', ''http'', ''https'',
                    ''oci'', ''file''])'
              verificationKey:

!important;\n}\n\n.align-content-stretch {\n  align-content: stretch !important;\n}\n\n.align-self-auto {\n  align-self: auto !important;\n}\n\n.align-self-start {\n  align-self: flex-start !important;\n}\n\n.align-self-end {\n  align-self: flex-end !important;\n}\n\n.align-self-center {\n  align-self: center !important;\n}\n\n.align-self-baseline {\n  align-self: baseline !important;\n}\n\n.align-self-stretch {\n  align-self: stretch !important;\n}\n\n@media (min-width: 576px) {\n  .flex-sm-row {\n    flex-direction:...

!important;\n}\n\n.align-content-stretch {\n  align-content: stretch !important;\n}\n\n.align-self-auto {\n  align-self: auto !important;\n}\n\n.align-self-start {\n  align-self: flex-start !important;\n}\n\n.align-self-end {\n  align-self: flex-end !important;\n}\n\n.align-self-center {\n  align-self: center !important;\n}\n\n.align-self-baseline {\n  align-self: baseline !important;\n}\n\n.align-self-stretch {\n  align-self: stretch !important;\n}\n\n@media (min-width: 576px) {\n  .flex-sm-row {\n    flex-direction:...

                                rule: '((has(self.operation) ? self.operation : '''')
                                  == ''UPSERT'') ? self.value != '''' : true'
                              - message: value must not be set when operation is REMOVE
                                rule: '((has(self.operation) ? self.operation : '''')
                                  == ''REMOVE'') ? !has(self.value) : true'

stretch{-ms-flex-line-pack:stretch!important;align-content:stretch!important}.align-self-auto{-ms-flex-item-align:auto!important;align-self:auto!important}.align-self-start{-ms-flex-item-align:start!important;align-self:flex-start!important}.align-self-end{-ms-flex-item-align:end!important;align-self:flex-end!important}.align-self-center{-ms-flex-item-align:center!important;align-self:center!important}.align-self-baseline{-ms-flex-item-align:baseline!important;align-self:baseline!important}.alig...

the Prism is feigned to be cut transversely through the middle of the
Light. Or if you please, let ABC represent the Prism it self, looking
directly towards the Spectator's Eye with its nearer end: And let XY be
the Sun, MN the Paper upon which the Solar Image or Spectrum is cast,
and PT the Image it self whose sides towards _v_ and _w_ are Rectilinear
and Parallel, and ends towards P and T Semicircular. YKHP and XLJT are

        StandardizedConv2D(tf.keras.layers.Conv2D): def call(self, inputs):
        mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,

}

def TF_SelfAdjointEigV2Op : TF_Op<"SelfAdjointEigV2", [Pure]> {
  let summary = [{
Computes the eigen decomposition of one or more square self-adjoint matrices.
  }];

  let description = [{
Computes the eigenvalues and (optionally) eigenvectors of each inner matrix in